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Deep_Privacy_For_Face_De_identification
People get their pictures taken on Google street view or when they pass by a journalist giving a report in public places, questions concerning the privacy of people visible arises. Among those image sources exposed to the public with or without our awareness, a considerable number of them contain our identity especially the bio-metric infor- mation. To solve these issue, we implement a model which can change a persons face to look like a completely different person, thus protecting their privacy. The model is trained with combination of generative adversarial networks(GAN) and autoencoders. We ensure anonymity by synthesizing GAN generated images. The generated faces are used to de-identify subjects in images or video, while preserving non-identity-related aspects of the data and consequently enabling data utilization.neural_hebbian_handwritten_recognition_mnist
Tensorflow: Neural Networks on Hebbian Learning rule applied for recognizing Handwritten digits on mnist datasettesorflow_convolution_neural_network
Created a convolution neural network using Tensorflow with multiple pooling and dense layers on CIFAR10 datasethadoop-graph-mapreduce
Hadoop Map-Reduce grouping nodes in graphopencv_harris_corner_detection
Image processing to obtain corner points in any image using harris corner algorithmMartrix-Multipy-MapReduce
Hadoop Martix Multiplication of two sparse matricesConnect-Components-graph-mapreduce
Parallel-Prime-Algorithm
Sieve of Eratosthenes Distributed Memory MPI Programopencv_boundry_hough_pattern_detection
Using opencv to apply Hough Transformation algorithm to detect pattern similar to train imageMatrix-Multiplication-Scala
Reinforcement_Learning_Multi_Armed_Bandit
Implementation of various multi-armed bandits algorithms using jupyter notebookTwitterClone
Twitter clone using React Native and aws amplifyOpinions
Opinions react native appmulti_threaded_client_server
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