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20142026
most citedHybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image Classification

1.9k citations · 3.4k across the 51 of their papers we have counts for

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Showing 2019Show all

11 papers · 1 filter

cs.CV2019

PSNet: Parametric Sigmoid Norm Based CNN for Face Recognition

Yash Srivastava, Vaishnav Murali, Shiv Ram Dubey

The Convolutional Neural Networks (CNN) have become very popular recently due to its outstanding performance in various computer vision applications. It is also used over widely st…

cs.LG2019★ 2 cited

NASIB: Neural Architecture Search withIn Budget

Abhishek Singh, Anubhav Garg, Jinan Zhou +2

Neural Architecture Search (NAS) represents a class of methods to generate the optimal neural network architecture and typically iterate over candidate architectures till convergen…

cs.LG2019

diffGrad: An Optimization Method for Convolutional Neural Networks

Shiv Ram Dubey, Soumendu Chakraborty, Swalpa Kumar Roy +3

Stochastic Gradient Decent (SGD) is one of the core techniques behind the success of deep neural networks. The gradient provides information on the direction in which a function ha…

cs.CV2019★ 5 cited

Visual Question Answering using Deep Learning: A Survey and Performance Analysis

Yash Srivastava, Vaishnav Murali, Shiv Ram Dubey +1

The Visual Question Answering (VQA) task combines challenges for processing data with both Visual and Linguistic processing, to answer basic `common sense' questions about given im…

cs.CV2019

Hard-Mining Loss based Convolutional Neural Network for Face Recognition

Yash Srivastava, Vaishnav Murali, Shiv Ram Dubey

Face Recognition is one of the prominent problems in the computer vision domain. Witnessing advances in deep learning, significant work has been observed in face recognition, which…

cs.CV2019

Spontaneous Facial Micro-Expression Recognition using 3D Spatiotemporal Convolutional Neural Networks

Sai Prasanna Teja Reddy, Surya Teja Karri, Shiv Ram Dubey +1

Facial expression recognition in videos is an active area of research in computer vision. However, fake facial expressions are difficult to be recognized even by humans. On the oth…