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Debapriya Hazra
Also published under:
Affiliation
Department of Computer Engineering, Jeju National University, Jeju, South Korea
Topic
Convolutional Layers,Convolutional Neural Network,Deep Learning,Deep Neural Network,Edge Detection,Image Edge,Image Inpainting,Input Image,Object Detection,Peak Signal-to-noise Ratio,Training Set,Transfer Learning,Absence Of Tumor,Adam Optimizer,Adversary Model,Affine Transformation,Bottled Water,Canny Edge Detection,Cerebrospinal Fluid,Classification Accuracy,Classification Results,Color Images,Computer Vision,Convolutional Network,DICOM Images,Data Augmentation,Deep Convolutional Neural Network,Edge Detection Algorithm,Edge Detection Method,Encoder Architecture,Encoder-decoder Network,Ensemble Method,Ensemble Model,F1 Score,Feature Maps,Feature Maps Of Images,Filters In Layer,Final Outcome,Fréchet Inception Distance,Generative Adversarial Network Architecture,Generative Adversarial Networks,Generative Adversarial Networks Model,Histogram,Illumination Conditions,Image Classification,Image Noise,Image Processing,Image Recognition,Image Regions,Image Size,
Biography
Debapriya Hazra received the B.Sc. degree (Hons.) in computer science, in 2012, and the M.C.A. degree in computer application, in 2015. Currently, she is pursuing the Ph.D. degree in machine learning with Jeju National University, South Korea. She worked at Atos Global IT Solutions and Services Pvt. Ltd. for three and a half years as a Software Engineer. Her current research interests include generative adversarial networks, image in painting, and medical image analysis in the field of machine learning.