most citedA Survey on Instance Segmentation: State of the art

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

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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.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.CV2020

Image Classification by Reinforcement Learning with Two-State Q-Learning

Abdul Mueed Hafiz

In this paper, a simple and efficient Hybrid Classifier is presented which is based on deep learning and reinforcement learning. Here, Q-Learning has been used with two states and…

cs.CV2020

Digit Image Recognition Using an Ensemble of One-Versus-All Deep Network Classifiers

Abdul Mueed Hafiz, Mahmoud Hassaballah

In multiclass deep network classifiers, the burden of classifying samples of different classes is put on a single classifier. As the result the optimum classification accuracy is n…

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…