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Sowmya, K. N.
- A Review on Use of Machine Learning Techniques in Diagnostic Health-Care
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Authors
Affiliations
1 JSS Academy of Technical Education, Bangalore, IN
1 JSS Academy of Technical Education, Bangalore, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 10, No 4 (2018), Pagination: 102-107Abstract
Monitoring of Physiological parameters/indicators of human body is indispensable in the health-care industry and in medical diagnosis. Today we find lot of invasive and non-invasive techniques adopted for vital data collection. The enormous amount of data/info thus obtained is used in predictive analytics for effective diagnosis of diseases, and plays an important role in life science. In this paper we provide a brief review of machine learning techniques adopted in predictive analysis for the challenging problems that the diagnostic health-care industry is exposed to today.
Keywords
Healthcare, Machine Learning, Predictive Analytics, Supervised Learning, Unsupervised Learning.References
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- Automatic Parking System using Vehicle License Plate Detection
Abstract Views :89 |
PDF Views:0
Authors
Affiliations
1 Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, IN
2 Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, IN
1 Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, IN
2 Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, IN
Source
Digital Image Processing, Vol 13, No 2 (2021), Pagination: 33-40Abstract
With phenomenal increase in the number of vehicles, vehicular systems and parking systems are a major challenge faced by urban cities. Parking systems currently rely on manual labour for noting down the registration numbers of vehicles entering the parking system. Our project aims at developing a parking system what would detect a vehicle while entering in the parking lot, and also would automatically recognize its registration number at day and night time. Parking lots are generally closed structures so there is always low light and at night time there are extremely low light conditions. Any camera would fail to provide noise free image at this condition. So there is need for low light enhancement. This paper discusses some of the existing low image enhancement algorithms. From the enhanced image, computation is done in detecting the vehicle, classifying it into4 wheelers or 2 wheeler vehicles and also extracting the registration number from the detected license plate. This paper deals with several existing architectures and models which perform ALPR on benchmark dataset.Keywords
ALPR, Low Light Enhancement, License Plate Detection, Character Recognition.References
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