90 Papers
204 Citations
Ayan Seal is an academic researcher from Indian Institute of Information Technology, Design and Manufacturing, Jabalpur. The author has contributed to research in topics: Computer science & Facial recognition system. The author has an hindex of 16, co-authored 66 publications. Previous affiliations of Ayan Seal include Jadavpur University & University of Hradec Králové.
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Papers
DeprNet: A Deep Convolution Neural Network Framework for Detecting Depression Using EEG
Ayan Seal,Rishabh Bajpai,Jagriti Agnihotri,Anis Yazidi,Enrique Herrera-Viedma,Ondrej Krejcar +5 more
TL;DR: In this paper, a DL-based convolutional neural network (CNN) called DeprNet was proposed for classifying the EEG data of depressed and normal subjects, where the Patient Health Questionnaire 9 score was used for quantifying the level of depression.
184
Facial Expression Recognition Using Local Gravitational Force Descriptor-Based Deep Convolution Neural Networks
TL;DR: In this article, a deep learning-based scheme is proposed for identifying the facial expression of a person, which consists of two parts: the former one finds out local features from face images using a local gravitational force descriptor, while, in the latter part, the descriptor is fed into a novel deep convolution neural network (DCNN) model.
153
A FPGA based implementation of Sobel edge detection
TL;DR: An architecture for Sobel edge detection on Field Programmable Gate Array (FPGA) board, which is inexpensive in terms of computation and reduces the time and space complexity compare to two existing architectures.
112
FER-net: facial expression recognition using deep neural net
TL;DR: This study proposes FER-net: a convolution neural network to distinguish FEs efficiently with the help of the softmax classifier and demonstrates that F ER-net is preeminent in comparison with twenty-one state-of-the-art methods.
104
Differential box counting methods for estimating fractal dimension of gray-scale images: A survey
TL;DR: The status of differential box counting methods is concluded, some of the state-of-the-art methods have been implemented and the possible future directions are explored.
104