most citedKisanQRS: A Deep Learning-based Automated Query-Response System for Agricultural Decision-Making

29 citations · 75 across the 10 of their papers we have counts for

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cs.CV202510 cited

A multi-temporal multi-spectral attention-augmented deep convolution neural network with contrastive learning for crop yield prediction

Shalini Dangi, Surya Karthikeya Mullapudi, Chandravardhan Singh Raghaw +3

Precise yield prediction is essential for agricultural sustainability and food security. However, climate change complicates accurate yield prediction by affecting major factors su…

cs.CV2025

Two Stage Context Learning with Large Language Models for Multimodal Stance Detection on Climate Change

Lata Pangtey, Omkar Kabde, Shahid Shafi Dar +1

With the rapid proliferation of information across digital platforms, stance detection has emerged as a pivotal challenge in social media analysis. While most of the existing appro…

cs.CV20256 cited

An Explainable Deep Neural Network with Frequency-Aware Channel and Spatial Refinement for Flood Prediction in Sustainable Cities

Shahid Shafi Dar, Bharat Kaurav, Arnav Jain +3

In an era of escalating climate change, urban flooding has emerged as a critical challenge for sustainable cities, threatening lives, infrastructure, and ecosystems. Traditional fl…

cs.CV20255 cited

A Multimodal-Multitask Framework with Cross-modal Relation and Hierarchical Interactive Attention for Semantic Comprehension

Mohammad Zia Ur Rehman, Devraj Raghuvanshi, Umang Jain +2

A major challenge in multimodal learning is the presence of noise within individual modalities. This noise inherently affects the resulting multimodal representations, especially w…

cs.CV202510 cited

ImpliHateVid: A Benchmark Dataset and Two-stage Contrastive Learning Framework for Implicit Hate Speech Detection in Videos

Mohammad Zia Ur Rehman, Anukriti Bhatnagar, Omkar Kabde +2

The existing research has primarily focused on text and image-based hate speech detection, video-based approaches remain underexplored. In this work, we introduce a novel dataset,…

cs.CV202516 cited

A Context-aware Attention and Graph Neural Network-based Multimodal Framework for Misogyny Detection

Mohammad Zia Ur Rehman, Sufyaan Zahoor, Areeb Manzoor +2

A substantial portion of offensive content on social media is directed towards women. Since the approaches for general offensive content detection face a challenge in detecting mis…