38 citations · 235 across the 22 of their papers we have counts for
12 papers · 1 filter
Uncertainty-aware Semi-supervised Ensemble Teacher Framework for Multilingual Depression Detection
Mohammad Zia Ur Rehman, Velpuru Navya, Sanskar +2
Detecting depression from social media text is still a challenging task. This is due to different language styles, informal expression, and the lack of annotated data in many langu…
A Multimodal Framework for Depression Detection during Covid-19 via Harvesting Social Media: A Novel Dataset and Method
Ashutosh Anshul, Gumpili Sai Pranav, Mohammad Zia Ur Rehman +1
The recent coronavirus disease (Covid-19) has become a pandemic and has affected the entire globe. During the pandemic, we have observed a spike in cases related to mental health,…
RoGBot: Relationship-Oblivious Graph-based Neural Network with Contextual Knowledge for Bot Detection
Ashutosh Anshul, Mohammad Zia Ur Rehman, Sri Akash Kadali +1
Detecting automated accounts (bots) among genuine users on platforms like Twitter remains a challenging task due to the evolving behaviors and adaptive strategies of such accounts.…
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…
Integrating Feedback Loss from Bi-modal Sarcasm Detector for Sarcastic Speech Synthesis
Zhu Li, Yuqing Zhang, Xiyuan Gao +4
Sarcastic speech synthesis, which involves generating speech that effectively conveys sarcasm, is essential for enhancing natural interactions in applications such as entertainment…
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…
An Adaptive Supervised Contrastive Learning Framework for Implicit Sexism Detection in Digital Social Networks
Mohammad Zia Ur Rehman, Aditya Shah, Nagendra Kumar
The global reach of social media has amplified the spread of hateful content, including implicit sexism, which is often overlooked by conventional detection methods. In this work,…
Emotion-aware Dual Cross-Attentive Neural Network with Label Fusion for Stance Detection in Misinformative Social Media Content
Lata Pangtey, Mohammad Zia Ur Rehman, Prasad Chaudhari +2
The rapid evolution of social media has generated an overwhelming volume of user-generated content, conveying implicit opinions and contributing to the spread of misinformation. Th…