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Abhishek, C.
- Indoor/Outdoor Alert Systems for the Blind
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Authors
Affiliations
1 Department of Electronics and Telecommunication Engineering, Silicon Institute of Technology, Bhubaneswar, IN
1 Department of Electronics and Telecommunication Engineering, Silicon Institute of Technology, Bhubaneswar, IN
Source
International Journal of Engineering Research, Vol 4, No SP 1 (2015), Pagination: 24-27Abstract
We present three IEEE papers introducing different indoor and outdoor alert systems for the blind. Though each paper is based on a different and new technology, they all aim towards providing a wireless electronic system for easy navigation of blind both in the domestic as well as outside environment. This paper describes the development and implementation of the projects undertaken based on the three papers. In the first paper a radio frequency based identification system (RFID) has been introduced which helps a university student to find his/her path using RFID tags and readers. The second paper introduces a prototype for the recognition of various sounds from different emergency alert systems in the domestic environment and notifying the blind-deaf person using vibro-tactile or electro-tactile sensor unit. The third paper describes the construction and evaluation of navigation system that infers the user's location using only magnetic sensing.Keywords
RFID, Audio-Analysis, Magnetic Sensing, RFID Tags, Vibro-Tactile, Electro-Tactile.- A Comprehensive Survey on Convolutional Neural Networks .
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Authors
C. Abhishek
1,
Vineeta
1
Affiliations
1 no, IN
1 no, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 13, No 3 (2021), Pagination: 37 - 42Abstract
Convolutional Neural Networks (CNN) is a unique category of Neural Network that has displayed promising results in Computer Vision and Image Processing. Computer Vision problems heavily depend on the features of the input data and the process of extracting those features. CNN provides a novel way of extracting those features with the help of filters and automatically learning them. CNN‟s are also used in a broad spectrum of applications, including but not limited to Image Classification, Image Segmentation, Object Detection, Speech Recognition, and others. This paper focuses on the comprehensive analysis of CNN components, types of activation functions, regularization techniques, and a brief study of the different CNN architectures.Keywords
Convolution Neural Network, GoogLeNet, ResNet, MobileNet.References
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- Cloud Based Solution for Skin Cancer Classification Using Machine Learning Models with Image Segmentation
Abstract Views :82 |
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Authors
Affiliations
1 Global Academy of Technology, Bangalore, IN
1 Global Academy of Technology, Bangalore, IN
Source
Digital Image Processing, Vol 13, No 4 (2021), Pagination: 61-64Abstract
According to the research 30,000 people are affected by skin cancer per year. Skin cancer is the unusual growth of skin cells. It occurs on the skin area which is exposed to sunlight. It is classified into two types - Melanoma or Benign. In our proposed work, we use deep learning concept in order to perform segmentation and classification of the lesions. We make use of the full resolution Convolutional Network (FrCN) to segment the skin cancer image. Then the segmented image is given as input to a deep residual network for classification.Keywords
No Keywords.References
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