A
Arijit Dey
Researcher at Indian Institute of Technology Madras
Publications - 46
Citations - 239
Arijit Dey is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Toric variety & Equivariant map. The author has an hindex of 7, co-authored 41 publications receiving 131 citations. Previous affiliations of Arijit Dey include Institute of Mathematical Sciences, Chennai & Islamic Azad University.
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A Hybrid Meta-Heuristic Feature Selection Method Using Golden Ratio and Equilibrium Optimization Algorithms for Speech Emotion Recognition
Arijit Dey,Soham Chattopadhyay,Pawan Kumar Singh,Ali Ahmadian,Massimiliano Ferrara,Ram Sarkar +5 more
TL;DR: This work proposes a meta-heuristic feature selection (FS) method using a hybrid of Golden Ratio Optimization (GRO) and Equilibriumoptimization (EO) algorithms, which it has named as Golden Ratio based Equilibrium optimization (GREO) algorithm.
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COVID-19 Detection by Optimizing Deep Residual Features with Improved Clustering-Based Golden Ratio Optimizer.
TL;DR: Wang et al. as discussed by the authors proposed a less expensive computational model for automatic COVID-19 detection from Chest X-ray and CT-scan images, which achieved state-of-the-art accuracies of 99.31, 98.65, and 99.44%, respectively.
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DRDA-Net: Dense residual dual-shuffle attention network for breast cancer classification using histopathological images
TL;DR: Chattopadhyay et al. as mentioned in this paper designed a dual-shuffle attention-guided deep learning model, called the dense residual dual-Shuffle attention network (DRDA-Net), which incorporated a channel attention mechanism to enhance the model's ability to learn the complex patterns of images.
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On Harder-Narasimhan reductions for Higgs principal bundles
TL;DR: The existence and uniqueness of H-N reduction for the Higgs principal bundles over nonsingular projective variety is shown in this article, and the notion of (Γ,G)-bundles and ramified G-bundle over a smooth curve is introduced.
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Tannakian classification of equivariant principal bundles on toric varieties
TL;DR: In this paper, the notion of compatible ∑-filtered vector space was introduced, where ∑ denotes the fan of a toric variety and G a reductive algebraic group defined over an algebraically closed field.