• Advancing text summarization with conscience, comprehension, and multimodality 

  Kumar, Yash; Goyal, Vikram (Advisor); Chakraborty, Tanmoy (Advisor) (IIIT-Delhi, 2024-01)

  Summarization, an essential technique for efficiently condensing extensive textual content into concise versions, has become increasingly valuable in the face of the information deluge characterizing the modern digital ...
• Deep learning-based Alzheimer’s disease diagnostics using medical images 

  Seraj, Mohammad; Murugan, N Arul (Advisor); Subramanyam, A V (Advisor) (IIIT-Delhi, 2024-05-01)

  In the ever-evolving landscape of medical innovation, the pursuit of accurate and efficient diagnostic tools for neurodegenerative diseases, notably Alzheimer's, has become increasingly urgent. The relentless progression ...
• Reducing test time using regression algorithms in post silicon validation 

  Mamodia, Shivani; Subramanyam, A V (Advisor) (IIIT-Delhi, 2020-07-01)
• Channel-graph regularized correlation filter for visual object tracking 

  Tyagi, Arjun; Subramanyam, A V (Advisor) (IIIT-Delhi, 2020-07-01)

  Correlation filter (CF) based tracker often disregard or weakly incorporate the importance of feature channels as well as channel similarity. To address this, we propose a channel-graph regularization correlation filter-based ...
• Sinkhorn attacks 

  Chaudhuri, Dibyendu Roy; Subramanyam, A V (Advisor) (IIIT-Delhi, 2021-07-01)

  Adversarial attacks have been extensively investigated in the recent past. Quite interestingly, a majority of these attacks primarily work in the lp space. In this work, we propose a novel approach for generating adversarial ...

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