most citedA Survey on Instance Segmentation: State of the art

501 citations · 511 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20203 cited

Reinforcement Learning Based Handwritten Digit Recognition with Two-State Q-Learning

Abdul Mueed Hafiz, Ghulam Mohiuddin Bhat

We present a simple yet efficient Hybrid Classifier based on Deep Learning and Reinforcement Learning. Q-Learning is used with two Q-states and four actions. Conventional technique…

cs.LG20202 cited

Deep Q-Network Based Multi-agent Reinforcement Learning with Binary Action Agents

Abdul Mueed Hafiz, Ghulam Mohiuddin Bhat

Deep Q-Network (DQN) based multi-agent systems (MAS) for reinforcement learning (RL) use various schemes where in the agents have to learn and communicate. The learning is however…

cs.CV20205 cited

Deep Network Ensemble Learning applied to Image Classification using CNN Trees

Abdul Mueed Hafiz, Ghulam Mohiuddin Bhat

Traditional machine learning approaches may fail to perform satisfactorily when dealing with complex data. In this context, the importance of data mining evolves w.r.t. building an…

cs.CV2020

Fast Training of Deep Networks with One-Class CNNs

Abdul Mueed Hafiz, Ghulam Mohiuddin Bhat

One-class CNNs have shown promise in novelty detection. However, very less work has been done on extending them to multiclass classification. The proposed approach is a viable effo…

cs.CV2020501 cited

A Survey on Instance Segmentation: State of the art

Abdul Mueed Hafiz, Ghulam Mohiuddin Bhat

Object detection or localization is an incremental step in progression from coarse to fine digital image inference. It not only provides the classes of the image objects, but also…