170 citations · 905 across the 84 of their papers we have counts for
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Deep learning powered real-time identification of insects using citizen science data
Shivani Chiranjeevi, Mojdeh Sadaati, Zi K Deng +10
Insect-pests significantly impact global agricultural productivity and quality. Effective management involves identifying the full insect community, including beneficial insects an…
Out-of-distribution detection algorithms for robust insect classification
Mojdeh Saadati, Aditya Balu, Shivani Chiranjeevi +5
Deep learning-based approaches have produced models with good insect classification accuracy; Most of these models are conducive for application in controlled environmental conditi…
Self-Attention Message Passing for Contrastive Few-Shot Learning
Ojas Kishorkumar Shirekar, Anuj Singh, Hadi Jamali-Rad
Humans have a unique ability to learn new representations from just a handful of examples with little to no supervision. Deep learning models, however, require an abundance of data…
Transductive Decoupled Variational Inference for Few-Shot Classification
Anuj Singh, Hadi Jamali-Rad
The versatility to learn from a handful of samples is the hallmark of human intelligence. Few-shot learning is an endeavour to transcend this capability down to machines. Inspired…
A Comprehensive Review on Recent Methods and Challenges of Video Description
Alok Singh, Thoudam Doren Singh, Sivaji Bandyopadhyay
Video description involves the generation of the natural language description of actions, events, and objects in the video. There are various applications of video description by f…
Explaining hyperspectral imaging based plant disease identification: 3D CNN and saliency maps
Koushik Nagasubramanian, Sarah Jones, Asheesh K. Singh +3
Our overarching goal is to develop an accurate and explainable model for plant disease identification using hyperspectral data. Charcoal rot is a soil borne fungal disease that aff…