DSpace at IIIT-Delhi: Recent submissions

  • On the distribution and applications of Ramanujan sums 
    Goel, Shivani; Chaubey, Sneha (Advisor) (IIIT-Delhi, 2024-05)
    While studying the trigonometric series expansion of certain arithmetic functions, Ramanujan, in 1918, defined a sum of the nth power of the primitive qth roots of unity and denoted it as cq(n). These sums are now known ...
  • Modeling online user interactions and their offline effects on socio-technical platforms 
    Hitkul; Shah, Rajiv Ratn (Advisor); Kumaraguru, Ponnurangam (Advisor) (IIIT-Delhi, 2024-03)
    Do online interactions trigger reactions back in the offline world? How can these reactions be detected and quantified? Specifically, what insights can be extracted for users, platform owners, and policymakers to minimize ...
  • Overcoming biases and injuries : tackling challenges in facial analytic systems 
    Majumdar, Puspita; Singh, Richa (Advisor); Vatsa, Mayank (Advisor) (IIIT-Delhi, 2024-06)
    The remarkable achievements and the robust performance of deep models have been instrumental in the evolution of facial analysis systems. Employed across a wide array of applications, these systems assist in making crucial ...
  • Language models for temporal decisions in health datasets 
    Pal, Ridam; Sethi, Tavpritesh (Advisor) (IIIT-Delhi, 2024-07)
    Healthcare has been undergoing a data-driven transformation, further accelerated by the COVID-19 pandemic. A significant amount of healthcare data is unstructured and underutilized. The success of Large Language Models ...
  • Audio visual consistency detection 
    Pathak, Harsh; Govil, Shreedhar; Subramanyam, A V (Advisor) (IIIT-Delhi, 2019-11-16)
    With recent advancement in deep learning, it has been made possible to create fake images and videos with near perfect precision. This has led to a growing concern about the possible misuse of this technology in context ...
  • Fine-grained unsupervised tracklet matching 
    Arora, Ansh; Subramanyam, A V (Advisor) (IIIT-Delhi, 2022-05)
    Re-identification offers a useful tool for non-invasive biometric validation, surveillance, and human-robot interaction in a broad range of applications from crowd traffic management to personalised healthcare. Given the ...
  • Subspace learning for person Re-identification 
    Roy, Neelabhro; Subramanyam, A V (Advisor) (IIIT-Delhi, 2019-11)
    Person Re-Identi cation (PRID) has been one of the most prominent problems in intelligent video surveillance in the recent past. PRID is the task of retrieving all the instances of a person given a single shot or a sequence ...
  • Semi dense adversarial LSTM for unsupervised video summarization 
    Sharma, Kunal; Chaudhary, Vipin; Subramanyam, A V (Advisor) (IIIT-Delhi, 2019-11)
    Video summarization is an important step in analysing video feeds in various scenarios such as surveillance, events and other applications. However, it is a challenging task due to inherent dynamic nature of video due to ...
  • Decoding the DNA of code: an AI-infused approach to detect code cloning in software systems 
    Mehrotra, Nikita; Purandare, Rahul (Advisor) (IIIT-Delhi, 2024-06)
    Code clones, duplicate code fragments sharing similar syntax or semantics, have become increasingly prevalent due to the success of software management tools like GitHub and advancements in Open Source Software (OSS). ...
  • Efficient surveillanve video compression using dictionary/transform learning 
    Nayeem, Mohammad; Subramanyam, A V (Advisor) (IIIT-Delhi, 2017-11-18)
    Techniques used for sparsifying the signal in dictionary or transform domain are quite popular in signal processing. In this work, we propose a method for e cient compression of surveillance videos. We observe that in these ...
  • Unsupervised cross-domain adaptation of person re-identification 
    Dhawan, Siddharth; Subramanyam, A V (Advisor) (IIIT-Delhi, 2019-11-16)
    Person re-identi cation is the task of retrieving images of a query person, from a gallery of images obtained from a non-overlapping camera network. Many supervised deep learning methods have been proposed for person ...
  • Empowering autism diagnosis : an artificial intelligence-assisted assessment in the Indian context 
    B, Ashwini; Shukla, Jainendra (Advisor) (IIIT-Delhi, 2024-03)
    The diagnostic process for Autism Spectrum Disorder (ASD) is complex,requiring extensive expertise to integrate information from diverse sourcessuch as parental reports and clinical observations. However, limited accessto ...
  • 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 ...
  • Unsupervised cross modality person Re-Identification 
    Gupta, Sagar; Subramanyam, A V (Advisor) (IIIT-Delhi, 2020-07-01)
    Unsupervised Person Re-Identi cation (Re-ID) su ers severely from the gap in the modality. Many factors pose a challenge to the task, including occlusions, lightning conditions, pose changes, among several others. Various ...
  • Disentangling reconstruction network for unsupervised cross-domain person Re-Identification 
    Jain, Harsh Kumar; Subramanyam, A V (Advisor) (IIIT-Delhi, 2020-06-01)
    Unsupervised cross-domain Person Re-Identi cation (Re-ID) severely su ers from the domain gap. While di erent works address this issue, bridging domain gap with high-level representation is hard as it comprises of entangled ...
  • On some special classes of additive codes over finite fields 
    Sharma, Sandeep; Sharma, Anuradha (Advisor) (IIIT-Delhi, 2024-05)
    In this thesis, we define and study a new class of additive codes over finite fields, viz. multi-twisted (MT) additive codes, which is a generalization of constacyclic additive codes and an extension of MT (linear) codes ...

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