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Co-Authors
- S. Vinothkumar
- P. Satheesh Kumar
- V. Sivaraj
- P. Manikandaprabhu
- C. Thirumoorthi
- M. Dev Anand
- G. Glan Devadhas
- N. Prabhu
- R. Krishnamoorthi
- R. Krishnamoorthy
- A. Rathinam
- K. Ramani
- T. K. Sumathi
- Dr. K. Kalaiselvi
- S. Kamaleshwar Rao
- V. Prashanth
- P. Nivas
- B. K. Jena
- K. S. Arunraj
- V. Suseentharan
- Tushar Kukadiya
- M. Ramkumar
- J. Gowrishankar
- V. Amirtha Preeya
- T. Pushpa
- Amirtha Preeya
- R. Manikandan
- Vidyabharathi Dakshinamurthi
- Syed Ibad Ali
- Nanda Satish Kulkarni
- Veeranan Arunprasad
- Brijendra Gupta
- Muruganantham Ponnusamy
Journals
- International Journal of Electronic and Electrical Engineering
- Programmable Device Circuits and Systems
- Digital Image Processing
- Indian Journal of Science and Technology
- ICTACT Journal on Image and Video Processing
- International Journal of Vehicle Structures and Systems
- International Journal of Innovative Research and Development
- International Journal of Advanced Networking and Applications
- Networking and Communication Engineering
- Current Science
- ICTACT Journal on Soft Computing
- ICTACT Journal on Communication Technology
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Karthikeyan, T.
- Automatic Indian Vehicle License Plate Recognition
Abstract Views :508 |
PDF Views:0
Authors
Affiliations
1 Dept of ECE. Aksheyaa College of Engineering, Puludivakkam, Kancheepuram, IN
1 Dept of ECE. Aksheyaa College of Engineering, Puludivakkam, Kancheepuram, IN
Source
International Journal of Electronic and Electrical Engineering, Vol 6, No 1 (2013), Pagination: 67-73Abstract
Automatic Vehicle License Plate Recognition has many applications in traffic systems (highway electronic toll collection, redlight violation enforcement, border and customs checkpoints, etc. Inthis project, a smart and simple algorithm is presented for vehicle’s license plate recognition system. The proposed algorithm consists of Four major parts: Image Pre Processing &Integral Edge Image, License Plate Localization, segmentation of the characters, recognition of the characters.Keywords
Character Recognizer, License Plate Recognition, Plateregion Extraction, Segmentation, Smearing, Template Matching, Matlab.
References
- Peter Tarabek, “Fast License Plate Detection based on Edge density and Integral Edge Image”, 10th International IEEE Jubilee International Symposium on Applied Machine Intelligence and Information, January 2012
- Rob.G.J. Wijnhoven and Peter H.N. de With “Identify Verification using Computer Vision for Automatic Garage Door Opening”, IEEE Transactions on consumer Electronics vol 57, No.2, May 2011
- Hinde ANOUAL, Sanna EL FKIHI, Abdellilah JILBAB, Driss ABOUTAJDINE “Vehicle License Plate Detection in Images”,International Conference onMultimedia Computing and Systems (ICMCS), 2011
- A.W. G. C.D Wijetunge and D.A.A.C.Ratnaweera “Real Time Recognition of License Plates of Moving Vehicles in Sri Lanka” 2011 6th International Conference on Industrial and information Systems, ICIIS 2011, 2011.
- Jianyu Zhao, Shujian Ma, WeiminHan, Yang Yang and Xudong Wang “Research and Implementation of License Plate Recognition”,Control and Decision Conference (CCDC), 2012
- ZuwenaMusoromy, Dr.SoodamaniRamalingam and NicoBekooy “Edge Detection Comparison for License Plate Detection”, 11thInt.Conf. Control, Automation, Robotics and Vision, 2010
- XiaojunZhai, FaycalBenssali and SoodamaniRamalingam “License Plate Localisation based on Morphological Operations” 11thInt.Conf. Control, Automation, Robotics and Vision, 2010
- Otsu N. “A Threshold Selection Method for Gray Level Histograms” IEEE Transactions on System, Man and Cybernetics, Vol.9, no. 1, PP 62-66, January 1979.
- A Single Phase Seven Level Inverter for Grid Connected Photovoltaic System by Employing PID Controller
Abstract Views :138 |
PDF Views:3
Authors
Affiliations
1 Mailam Engineering College, Villupuram, IN
1 Mailam Engineering College, Villupuram, IN
Source
Programmable Device Circuits and Systems, Vol 4, No 10 (2012), Pagination: 480-483Abstract
This paper presents a single phase seven level photovoltaic (PV) inverter topology for grid connected PV systems with a novel Pulse Width Modulated (PWM) control scheme. Three reference signals identical to each other with an offset equivalent to the amplitude of the triangular carrier signal were used to generate PWM signals for the switches. A digital Proportional-Integral derivative (PID) current control algorithm is implemented in MICROCONTROLLER PIC16C7F88 to keep the current injected into the grid sinusoidal and to have high dynamic performance with rapidly changing atmospheric conditions. The inverter offers much less total harmonic distortion and can operate at near-unit power factor. The proposed system is verified through simulation and is implemented in a prototype. Experimental results are compared with the conventional single phase five level grid connected PWM inverter.Keywords
Grid Connected Photovoltaic System, Single Phase Seven Level Inverter, Maximum Power Point Tracking System and Proportional-Integral Derivative (PID) Controller.- A New Keyword and Content-Based Image Retrieval by Clustering
Abstract Views :163 |
PDF Views:2
Authors
V. Sivaraj
1,
T. Karthikeyan
2
Affiliations
1 CiiT Academic Research Lab, Coimbatore, IN
2 PSGCAS, Coimbatore, IN
1 CiiT Academic Research Lab, Coimbatore, IN
2 PSGCAS, Coimbatore, IN
Source
Digital Image Processing, Vol 2, No 5 (2010), Pagination: 180-184Abstract
The CLUster-based rEtrieval(CLUE), groups the image based on the similarity measure, so that there is maximum similarity with in the cluster and minimum similarity between the two cluster and then retrieve the images related to the query. The cluster based retrieval of images tackles the semantic gap problem. The Content-Based Image Retrieval (CBIR) extract the feature of the images and the images with maximum similarity with that of the query is retrieved. This paper makes use of both the concept to retrieve the images. The CBIR system-using CLUE is called as Content-Based Image Clusters Retrieval (CBICR). The keyword-based retrieval along with the CBIR system retrieves the relevant images more effectively and it consumes less amount of time. The keyword based retrieval is done and the Nearest Neighbor Method is used to locate neighbor of the target image. The N-cut algorithm is used to organize the cluster.- Embedded Zero Tree Wavelet based Artificial Neural Network Image Classification Algorithm - A Study
Abstract Views :191 |
PDF Views:0
Authors
Affiliations
1 PG and Research Department of Computer Science, PSG College of Arts and Science, Coimbatore - 641014, Tamil Nadu, IN
1 PG and Research Department of Computer Science, PSG College of Arts and Science, Coimbatore - 641014, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 20 (2015), Pagination:Abstract
In this work, an urban area land cover is proposed to classify the large resolution image. It aims to extract the features like texture, shape, size and spectral information in the feature extraction process. Embedded Zero tree Wavelet transform is a lossy image compression algorithm. Most of the coefficients at low bit rates bent through a sub band transform will be zero, or very close to zero. These features data are used for the classification process. Here, we used various classification algorithms namely, Radial Basis Function, SMO, Multilayer Perceptron and Random Forest are implemented. The classification accuracy constantly depends on the efficiency of the extracted features and classification algorithms. The result of the proposed classification algorithms are merged with EZW. Experimental results illustrate that the better accuracy performance is obtained by the Multilayer Perceptron algorithm than other classification algorithms.Keywords
Artificial Neural Network, Embedded Zero Tree Wavlet, Feature Extraction, Image Classification, Multilayer Perceptron, Radial Basis FunctionFull Text
- A Hybrid Medical Image Compression Techniques for Lung Cancer
Abstract Views :205 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science, PSG College of Arts and Science, Coimbatore, IN
2 Department of Computer Science, Hindustan College of Arts and Science, Coimbatore, IN
1 Department of Computer Science, PSG College of Arts and Science, Coimbatore, IN
2 Department of Computer Science, Hindustan College of Arts and Science, Coimbatore, IN
Source
Indian Journal of Science and Technology, Vol 9, No 39 (2016), Pagination:Abstract
Objectives: This study focuses on Image compression and compares different methods. Methods/Statistical Analysis: In this work we simulated four image compression methods. The first method is focused on Karhunen-Loève Transforms (KLT), second method is focused on Walsh-Hadamard Transforms (WHT), third method based on FFT and fourth one is proposed sFFT. Findings: The experimental outcomes are compared with the different quality of parameters applying on numerous lung cancers CT scan images. The Proposed SFFT method algorithm was given better results like Peak Signal to Noise Ratio (PSNR), Structural Content (SC), Mean Square Error (MSE) and Compression Ratio (CR) are compare to other Transform methods. Application /Improvement: The Proposed SFFT technique gives improved result compared with other methods in all evaluation measures.Keywords
CR, FFT, Image Compression, KLT, Lung Cancer CT Images, MSE, PSNR, Proposed sFFT, SC, WHT.Full Text
- Ceramic Monolith Heat Exchanger - A Theoretical Study and Performance Analysis
Abstract Views :198 |
PDF Views:0
Authors
Affiliations
1 Department of Mechanical Engineering, Noorul Islam Centre for Higher Education, Kumaracoil - 629 180, Thuckalay, Kanyakumari District, Tamil Nadu, IN
2 Department of Electronics and Instrumentation Engineering, Noorul Islam University, Kumaracoil - 629 180, Thuckalay, Kanyakumari District, Tamil Nadu, IN
3 Department of Mechanical Engineering, Kottayam Institute of Technology and Science (KITS), Chengalam East, Pallickathodu, Kottayam - 686585, Kerala, IN
4 Department of Mechanical Engineering, Saveetha Nagar, Thandalam, Chennai - 602105, Tamil Nadu, IN
1 Department of Mechanical Engineering, Noorul Islam Centre for Higher Education, Kumaracoil - 629 180, Thuckalay, Kanyakumari District, Tamil Nadu, IN
2 Department of Electronics and Instrumentation Engineering, Noorul Islam University, Kumaracoil - 629 180, Thuckalay, Kanyakumari District, Tamil Nadu, IN
3 Department of Mechanical Engineering, Kottayam Institute of Technology and Science (KITS), Chengalam East, Pallickathodu, Kottayam - 686585, Kerala, IN
4 Department of Mechanical Engineering, Saveetha Nagar, Thandalam, Chennai - 602105, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 13 (2016), Pagination:Abstract
A ceramic monolith heat exchanger has been learnt for finding out heat transfer performance and effectiveness on computing numerically and ξ-NTU method. In entire domain computation numerically has been performed along with fluid region in rectangular ducts of exhaust gas side, ceramic core and rectangular duct fluid region in air side with the air exhaust in direction of cross flow. Additionally, the heat exchanger has been examined for estimating the functionality via ξ-NTU technique that is conventional along numerous Nusselt number links for rectangular duct flow for the literature. Based on the research, it has been performed on the ceramic heat exchangers and on the ceramic materials and the demand in utilizing the ceramic materials in heat exchangers. Then the recuperator is modeled by using GAMBIT and it is analyzed using FLUENT. The effectiveness and the heat transfer rate are also calculated. Then those outcomes have been assessed along the experimental data. By comparison of both functionality by computing numerically and the ξ-NTU technique, the efficiency by ξ-TU technique has been identified to be nearest to product by the numerical computation among the associative of 2.15% when Stephan's Nusselt number association has been adapted to the ξ-NTU technique within numerous connections. The total heat transfer and effectiveness by ξ-NTU method relative errors utilizing five Nusselt number correlations from literature have been lesser than 14.5% comparative to numerical computation. Associated to Nusselt number correlations, the entire heat transfer utilizing ξ-NTU technique with Stephan's correlation is highly nearest to numerical computation. For that reason, the exit temperature by ξ-NTU method with Stephan's correlation simulates within 1.2% of the relative error for exhaust exist temperature and 0.45% for the air exit temperature assessed against the numerical computation. Overall heat transfer coefficient's relative errors by ξ-NTU technique utilizing five Nusselt number correlations for the literature have been more than 17.5% to that on computing numerically.Keywords
Ceramic Recuperators, Cross Flow, Effectiveness, Heat Transfer, Pressure DropFull Text
- Texture Preserving Image Coding Using Orthogonal Polynomials
Abstract Views :150 |
PDF Views:1
Authors
Affiliations
1 Department of Information Technology, Bharathidasan Institute of Technology, Trichy, Tamil Nadu, IN
2 Department of Computer Science and Engineering, PSG College of Arts and Science, Coimbatore, Tamil Nadu, IN
1 Department of Information Technology, Bharathidasan Institute of Technology, Trichy, Tamil Nadu, IN
2 Department of Computer Science and Engineering, PSG College of Arts and Science, Coimbatore, Tamil Nadu, IN
Source
ICTACT Journal on Image and Video Processing, Vol 1, No 1 (2010), Pagination: 32-36Abstract
In order to replace the artifacts in the textured background, a new texture preserving image coder using the set of orthogonal polynomials is proposed in this paper. The proposed scheme is based on the model that represents textures using points spread operator relating to a linear system. In the proposed texture based image coding scheme, the encoder first identifies textured regions, which are then analyzed to produce the model features. Then these features are later transmitted to decoder which decodes to form a synthetic texture and results into synthetic stage. The proposed modeling delivers to attain high compression ratio by maintaining constantly excellent visual quality. 92.31% with a PSNR value of 31.93dB when the quality factor is 5 for D96 image is achieved by the proposed scheme. By keeping up the quality factor as a constant constrained, we obtain 91.11% of compression ratio with a PSNR value of 33.26dB for different set of image that is, D38 image.Keywords
Texture Preserving Image Coder, Points Spread Operator, Synthetic Texture, Texture Modeling and Compression Ratio.- Autoregressive Model Based on Bayesian Approach for Texture Representation
Abstract Views :170 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science, PSG College of Arts and Science, IN
2 Department of Computer Science and Engineering, Anna University, Tiruchirappalli, IN
1 Department of Computer Science, PSG College of Arts and Science, IN
2 Department of Computer Science and Engineering, Anna University, Tiruchirappalli, IN
Source
ICTACT Journal on Image and Video Processing, Vol 3, No 1 (2012), Pagination: 485-491Abstract
In this study autoregressive model based on Bayesian approach is proposed for texture classification. Based on auto correlation coefficients, micro textures are identified and represented locally and then globally. The identified micro texture is represented as a local description, called texnum. The global descripter, texspectnum, is obtained by simply observing the numbers of occurrences of the texnums that cover the entire image. The proposed representation scheme has been employed in both supervised and unsupervised classifications of textured images. The supervised classification is based on simple tests of hypotheses and the unsupervised classification is based on the modified K-means algorithm with minimum distance classifiers. The proposed method is demonstrated for classification of different types natural textured images. The average correct classification is better than the existing methods.Keywords
Texnum, Texspectnum, Microtexture, K-Means Algorithm, Supervised and Unsupervised Classification.- Electric Vehicle by using Modified Topology of Multilevel Inverter
Abstract Views :240 |
PDF Views:113
Authors
Affiliations
1 Dept. of Electrical and Electronics Engg., Paavai Engg. College, Namakkal, Tamilnadu, IN
2 Dept. of Mech. Engg., M. Kumarasamy College of Engg., Karur, Tamilnadu, IN
3 Dept. of Electrical and Electronics Engg., Universiti Teknologi Petronas, Perak, MY
1 Dept. of Electrical and Electronics Engg., Paavai Engg. College, Namakkal, Tamilnadu, IN
2 Dept. of Mech. Engg., M. Kumarasamy College of Engg., Karur, Tamilnadu, IN
3 Dept. of Electrical and Electronics Engg., Universiti Teknologi Petronas, Perak, MY
Source
International Journal of Vehicle Structures and Systems, Vol 9, No 1 (2017), Pagination:Abstract
This paper focused with extends the knowledge in studies and analysis of a new family of diode clamp multilevel inverter for electric vehicle application. The modified new diode clamp multilevel inverter concepts is related to reducing the components utilization, which has (n-1) switching devices, (n-3) clamping diodes, (n-1)/2 DC-link sources for achieving the same voltage level of traditional topologies. The proposed system is enhanced the voltage rating and reduce the total harmonics distortion in inverter output voltage. The switching scheme of Alternatively on Opposition Disposition pulse width modulation strategies is implemented to control multilevel inverter. The proposed system reduces the components utilization which has utilizes 45% of components for achieving the same level of voltage. The modified new diode clamp multilevel inverter is coupled with induction motor and its performance is validated with three phase induction motor for variable frequency drive. The inverter topologies performance has been investigated by prototype model.Keywords
Multilevel Inverter, APO-PWM, Induction Motor, Total Harmonic Distortion, Topology.Full Text
References
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- H. Liu, Y. Zhang, Q. Zheng, D. Wang and S. Guo. 2007.Design and simulation of an inverter-fed induction motor for electric vehicles, Proc. Vehicle Power and Propulsion Conf., IEEE 112-115. https://doi.org/10.1109/vppc.2007.4544109.
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- M.M. Renge and H.M. Suryawanshi. 2008. 5-level diode clamped inverter to eliminate common mode voltage and reduce dv/dt in medium voltage rating induction motor drives, IEEE Trans. Power Electron., 23(4), 1598-1607. https://doi.org/10.1109/TPEL.2008.925423.
- J. Redriguez, S. Bernet, P.K. Steimer and I.E.Lizama. 2010. A survey on neutral point clamped inverter, IEEE Trans. Ind. Electron., 57(7), 2219-2230. https://doi.org/ 10.1109/TIE.2009.2032430.
- M. Malinowski, K. Gopakumar, J. Rodriquez and M.A.Perez. 2010. A survey on cascaded multilevel inverters, IEEE Trans. Ind. Electron., 57(7), 2197-2206.https://doi.org/10.1109/TIE.2009.2030767.
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- K.K. Gupta and S. Jain. 2014. A novel multilevel inverter based on switched DC sources, IEEE Trans. Ind.Electron., 61(7), 3269-3278. https://doi.org/10.1109/TIE.2013.2282606.
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- M.F. Kangaylu and E. Babaei. 2013. A generalized cascaded multilevel inverter using series connection of sub multilevel inverter, IEEE Trans. Power Electron., 28(2), 625-636. https://doi.org/10.1109/TPEL.2012.2203339.
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- Multi-Biometric Personal Authentication with 3d Face and Iris Images Using Sum Rule Based Fusion of Matching Scores
Abstract Views :179 |
PDF Views:6
Authors
Source
International Journal of Innovative Research and Development, Vol 3, No 11 (2014), Pagination:Abstract
In this paper we propose a multi-biometric system for personal authentication with two biometric traits using image fusion after matching. Regardless of significant advances in the latest years, there are still several limitations derived from utilizing one biometric trait. The problem with a unimodal biometric verification system is that since it uses only a single biometric trait it suffers from the disadvantages such as lack of universality, interclass variation and sensitivity to attacks which lead to spoofing of the authentication system. In order to overcome these shortcomings, multi- biometric systems are introduced. In this paper the combination of iris and face biometric authentication system is implemented and analyzed with several matching score level fusion techniques. In the system, a dynamic 3D face verification and improved iris segmentation and verification are developed and they are fused using sum rule based matching scores fusion technique.
Keywords
Biometrics, sum rule, image fusion, matching scores, 3D face, irisFull Text
- Efficient Bio Metric IRIS Recognition System Using Fuzzy Neural Network
Abstract Views :112 |
PDF Views:0
Authors
Affiliations
1 PSG College of Arts and Science, Coimbatore, IN
1 PSG College of Arts and Science, Coimbatore, IN
Source
International Journal of Advanced Networking and Applications, Vol 1, No 6 (2010), Pagination: 371-376Abstract
The High protection mechanism and security is very essential things in a grow of computer world. Biometric Authentication is in rider seat of the computer society. Authentication and security based on “what you are?” rather than what you have? Like Identity Card, Physical Key and what you know? Like Password. Iris recognition a relatively new biometric technology, has great advantages, such as variability, stability and security, thus it is the most promising for high security environments. To determine the performance and recognition system a database grayscale eye images were used. Iris is part of eye between eyelids and surrounding. Four different algorithms were designed for verifying Irises viz., 1. Circular-Mellin algorithm, 2. Canny edge detection algorithm, these two algorithms are used for detect the Iris boundaries, 3. Harr wavelet algorithm, 4. Embedded-tree zero wavelet algorithms, 5. Fuzzy neural network algorithm used to extract the deterministic patterns in a person’s Iris in the form of feature vector. Identity is done with the help of the Hamming Distance operator.Full Text
- Information Hiding Using Temporally Brightness Modulated Pattern
Abstract Views :163 |
PDF Views:0
Authors
Source
Networking and Communication Engineering, Vol 10, No 7 (2018), Pagination: 140-142Abstract
A new display system technology that may hide secret data behind a displayed image, whereas at the same time satisfying each high physical property and readability needs. The hidden data may be a reasonably binary image as well as characters, and varied varieties of patterns, i.e., Quadratic Residue (QR) codes. This system uses a temporally bright modulated invisible pattern in an exceedingly moving image, or video. Frame pictures over some period’s area unit summed up once scan out, enhancing the distinction of the invisible pattern to create it visible. We have a tendency to conjointly propose a replacement technique to unravel a problem that happens thanks to asynchronous operations of the show and video camera that may be a technique that was achieved by mistreatment time shift sampling. The hidden binary image scans out per experiments that we conducted to substantiate the results. Moreover, the patterns employed in this system were in spades invisible once arranged behind the most pictures, that steered the planned technology was extremely possible in sensible applications per this confirmation. At the decoder facet, a robust two-class SVM classifier is meant to tell apart encrypted and unencrypted image patches, permitting North American country to put together rewrite the embedded message and therefore the original image signal. Compared with the progressive ways, the planned approach provides higher embedding capability and is ready to dead reconstruct the first image likewise because the embedded message.
Keywords
Quadratic Residue (QR) Codes, Bright Modulated Invisible Pattern- Indian Coastal Ocean Radar Network
Abstract Views :268 |
PDF Views:77
Authors
Affiliations
1 Coastal and Environmental Engineering Division, National Institute of Ocean Technology, Chennai - 600 100, IN
1 Coastal and Environmental Engineering Division, National Institute of Ocean Technology, Chennai - 600 100, IN
Source
Current Science, Vol 116, No 3 (2019), Pagination: 372-378Abstract
As a part of the Indian Ocean Observation Network, National Institute of Ocean Technology operates and maintains a network of high frequency radar (HFR) systems along the Indian coast, known as Indian coastal ocean radar network (ICORN). It is a land-based remote sensing system capable of measuring surface currents as far as 200 km from the coast and waves, and wind direction nearly 100 km offshore. The HFR systems utilize electromagnetic waves in the 3-45 MHz frequency band and use Bragg scattering principle to deduce the oceanographic parameters. ICORN currently operates and maintains five pairs (10 sites) of long-range systems (∼5 MHz) which covers four states and Andaman and Nicobar Islands. These systems operate at a spatial resolution of 6 km and temporal resolution of one hour. Indian National Centre for Ocean Information Services at Hyderabad disseminates this data for scientific and maritime operations. The potential of HFR systems is enormous and can be employed in various facets of operational oceanography and applied research.Keywords
HF Radar, EICC, ICORN, Surface Currents, Waves.Full Text
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- Gene Biclustering On Large Datasets Using Fuzzy C-means Clustering
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Authors
Affiliations
1 Department of Computer Science and Engineering, HKBK College of Engineering, IN
2 Department of Computer Science and Engineering, Jain University, IN
3 Department of Computer Science and Engineering, Presidency University, IN
4 Department of Electronics and Telecommunications Engineering, University of Technology and Applied Sciences, OM
1 Department of Computer Science and Engineering, HKBK College of Engineering, IN
2 Department of Computer Science and Engineering, Jain University, IN
3 Department of Computer Science and Engineering, Presidency University, IN
4 Department of Electronics and Telecommunications Engineering, University of Technology and Applied Sciences, OM
Source
ICTACT Journal on Soft Computing, Vol 12, No 2 (2022), Pagination: 2578-2582Abstract
The current study employs biclustering to alleviate some of the drawbacks associated with gene expression data grouping. Different biclustering algorithms are used in this study to detect unique gene activity in various contexts and reduce the duplication of broad gene information. Furthermore, machine learning or heuristic algorithms have become widely utilised for biclustering due to their suitability in problems where populations of potential solutions allow examination of a larger percentage of the research area. To begin with, gene expression data biclusters frequently contain data that is the same under a variety of different situations of gene expression. Therefore, the biclustering technique is particularly effective if the matrix lines and columns are merged immediately. Submatrices can be identified using the Large Average Sub matrix. A Fuzzy C-Means algorithm is also used to ensure that the sub-matrix can be expanded to include more rows and columns for further analysis. The sub-matrices and component precision and strength are factored into the system design. It uses biclustering techniques to differentiate gene expression information. On the Garber dataset, the simulation is run in Java. Using the average match score for non-overlapping modules, the influence of noise on overlapping modules using constant bicluster and additive bicluster, and the overall run duration, the study is assessed.Keywords
Heuristic Algorithm, Gene Expression, Data Biclusters, Fuzzy C-MeansReferences
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- IRIS Detection For Biometric Pattern Identification Using Deep Learning
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Authors
Affiliations
1 Department of Computer Science and Engineering, HKBK College of Engineering, IN
2 Department of Computer Science and Engineering, Presidency University, IN
3 Department of Computer Science, The Quaide Milleth College for Men, IN
4 Department of Electronics and Telecommunications Engineering, University of Technology and Applied Sciences, OM
1 Department of Computer Science and Engineering, HKBK College of Engineering, IN
2 Department of Computer Science and Engineering, Presidency University, IN
3 Department of Computer Science, The Quaide Milleth College for Men, IN
4 Department of Electronics and Telecommunications Engineering, University of Technology and Applied Sciences, OM
Source
ICTACT Journal on Image and Video Processing, Vol 12, No 2 (2021), Pagination: 2610-2614Abstract
In this paper, we develop a liveness detection of iris present in the study to reduce various spoofing attacks using gray-level co-occurrence matrix (GLCM) and Deep Learning (DL). The input images of iris are been given to this technique for the extraction of texture and colour features with fine details. The details are fused finally and given to a DL classifier for the classification of liveness detection. The simulation is conducted to test the efficacy of the model and the results of simulation shows that the proposed method achieves higher level of accuracy than existing methods.Keywords
Iris Detection, Pattern Identification, Liveness Detection, Biometric, Deep LearningReferences
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- Causal Convolution Employing Almeida–Pineda Recurrent Backpropagation for Mobile Network Design
Abstract Views :46 |
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Authors
Affiliations
1 Department of Computer Science and Engineering, Sona College of Technology, IN
2 School of Engineering, Ajeenkya DY Patil University, IN
3 Department of Information Technology, University of Technology and Applied Sciences - Salalah, OM
4 Department of Electronics and Telecommunication Engineering, Siddhant College of Engineering, IN
1 Department of Computer Science and Engineering, Sona College of Technology, IN
2 School of Engineering, Ajeenkya DY Patil University, IN
3 Department of Information Technology, University of Technology and Applied Sciences - Salalah, OM
4 Department of Electronics and Telecommunication Engineering, Siddhant College of Engineering, IN
Source
ICTACT Journal on Communication Technology, Vol 14, No 4 (2023), Pagination: 3091-3096Abstract
Designing efficient mobile networks is crucial for meeting the growing demand for high-speed, reliable communication. However, existing convolutional neural network (CNN) architectures face challenges in capturing temporal dependencies, hindering their performance in mobile network design. The introduction highlights the increasing importance of mobile networks and identifies the limitations of current CNN architectures in capturing temporal dynamics. The problem statement emphasizes the need for an enhanced model that can effectively address temporal dependencies in mobile network design. This research addresses this problem by proposing a novel approach: Causal Convolution employing Almeida–Pineda Recurrent Backpropagation (CC-APRB). The causal convolution captures temporal dependencies by considering only past and present inputs, while the recurrent backpropagation optimizes the model parameters based on sequential data. The integration of these techniques aims to enhance the model ability to capture temporal features in mobile network data. The results indicate significant improvements in the performance of the CC-APRB model compared to traditional CNN architectures. The model demonstrates enhanced accuracy and efficiency in capturing temporal dependencies, making it well-suited for mobile network design applications.Keywords
Causal Convolution, Almeida–Pineda Recurrent Backpropagation, Mobile Network Design, Temporal Dependencies, Deep Learning.References
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- Hybrid Neuro-fuzzy-genetic Algorithms for Optimal Control of Autonomous Systems
Abstract Views :23 |
PDF Views:2
Authors
Affiliations
1 Department of Mechanical Engineering, Theni Kammavar Sangam College of Technology, IN
2 Department of Information Technology, Siddhant College of Engineering, IN
3 Department of Information Technology, University College of Technology and Applied Sciences - Salalah, OM
4 Indian Institute of Information Technology Kalyani, IN
1 Department of Mechanical Engineering, Theni Kammavar Sangam College of Technology, IN
2 Department of Information Technology, Siddhant College of Engineering, IN
3 Department of Information Technology, University College of Technology and Applied Sciences - Salalah, OM
4 Indian Institute of Information Technology Kalyani, IN
Source
ICTACT Journal on Soft Computing, Vol 13, No 4 (2023), Pagination: 3015-3020Abstract
In recent years, there has been an increasing demand for efficient and robust control algorithms to optimize the performance of autonomous systems. Traditional control techniques often struggle to handle the complexity and uncertainty associated with such systems. To address these challenges, hybrid neuro-fuzzy-genetic algorithms have emerged as a promising approach. This paper presents a comprehensive review of the application of hybrid neuro-fuzzy-genetic algorithms for optimal control of autonomous systems. The proposed algorithms combine the strengths of neural networks, fuzzy logic, and genetic algorithms to achieve adaptive and optimal control in real-time scenarios. The neuro-fuzzy component provides the ability to model and handle complex and uncertain systems, while the genetic algorithm component facilitates the optimization of control parameters. The combination of these techniques enables autonomous systems to adapt and optimize their control strategies based on changing environments and objectives. The paper discusses the underlying principles of hybrid neuro-fuzzy-genetic algorithms, their advantages, and challenges. It also provides a review of the state-of-the-art research in this field, highlighting successful applications and potential future directions. Overall, the integration of neuro-fuzzy-genetic algorithms in autonomous systems holds great promise for achieving optimal control in various domains, including robotics, aerospace, and autonomous vehicles.Keywords
Hybrid Algorithms, Neuro-Fuzzy-Genetic Algorithms, Optimal Control, Autonomous Systems, Neural Networks, Fuzzy Logic, Genetic Algorithms, Real-Time Control, Adaptive Control, Uncertainty, Robotics, Aerospace, Autonomous Vehicles.References
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