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20242026
most citedA Multimodal Framework for Depression Detection during Covid-19 via Harvesting Social Media: A Novel Dataset and Method

37 citations · 74 across the 6 of their papers we have counts for

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Showing 2025Show all

14 papers · 1 filter

cs.CL2025

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…

cs.AI202537 cited

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,…

cs.SI2025

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.…

cs.CY202527 cited

A social context-aware graph-based multimodal attentive learning framework for disaster content classification during emergencies: a benchmark dataset and method

Shahid Shafi Dar, Mohammad Zia Ur Rehman, Karan Bais +2

In times of crisis, the prompt and precise classification of disaster-related information shared on social media platforms is crucial for effective disaster response and public saf…

cs.CV202510 cited

A Comprehensive Survey of Mamba Architectures for Medical Image Analysis: Classification, Segmentation, Restoration and Beyond

Shubhi Bansal, Sreeharish A, Madhava Prasath J +6

Mamba, a special case of the State Space Model, is gaining popularity as an alternative to template-based deep learning approaches in medical image analysis. While transformers are…

cs.CV2025

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…