38 citations · 235 across the 22 of their papers we have counts for
6 papers · 2 filters
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…
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…
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…
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,…
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…
T-MPEDNet: Unveiling the Synergy of Transformer-aware Multiscale Progressive Encoder-Decoder Network with Feature Recalibration for Tumor and Liver Segmentation
Chandravardhan Singh Raghaw, Jasmer Singh Sanjotra, Mohammad Zia Ur Rehman +3
Precise and automated segmentation of the liver and its tumor within CT scans plays a pivotal role in swift diagnosis and the development of optimal treatment plans for individuals…