Year-2023

 

Recent Submissions

  • Identify, inspect and intervene multimodal fake news 
    Singhal, Shivangi; Shah, Rajiv Ratn (Advisor); Kumaraguru, Ponnurangam (Advisor) (IIIT-Delhi, 2023-06)
    Fake news refers to intentionally and verifiably false stories created to manipulate people’s perceptions of reality. Fake news is destructive and has been used to influence voting decisions and spread hatred against ...
  • Leveraging machine learning in identification of biomarkers for cancer diagnosis and personalized therapy recommendation 
    Goswami, Chitrita; Sengupta, Debarka (Advisor) (IIIT-Delhi, 2023-02)
    In an era where machine learning (ML) is changing the landscape of financial markets, education, security and privacy, the retail sector, and many other crucial aspects of human life, it is only fitting that we should use ...
  • Algorithms for spatial colocation pattern mining 
    Baride, Srikanth; Goyal, Vikram (Advisor) (IIIT-Delhi, 2023-12)
    Spatial data mining is a specialized field that focuses on extracting meaningful insights and patterns from geographical or spatial data. One particular area of interest in spatial data mining is colocation pattern mining. ...
  • Deep clustering 
    Goel, Anurag; Majumdar, Angshul (Advisor) (IIIT-Delhi, 2023-11)
    The traditional way of clustering is first extracting the feature vectors according to domain-specific knowledge and then employing a clustering algorithm on the extracted features. Deep learning approaches attempt to ...
  • On heterogeneous face recognition 
    Ghosh, Soumyadeep; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) (IIIT-Delhi, 2023-03)
    Face recognition under controlled and constrained scenarios have reached a significant level of maturity with respect to performance and reliability. However, under unconstrained and un controlled settings, current ...
  • Information fusion using convolutional transform learning 
    Gupta, Pooja; Majumdar, Angshul (Advisor) (IIIT-Delhi, 2023-09)
    There are many real-world problems pertaining to the need for the fusion of information from multiple sources. Consider, for example, the problem of demand forecasting that requires estimating the power consumption at a ...
  • A study on smooth activation functions 
    Biswas, Koushik; Pandey, Ashish Kumar (Advisor); Banerjee, Shilpak (Advisor) (IIIT-Delhi, 2023-07)
    Artificial neural networks (ANNs) have occupied the centre stage in deep learning. An activation function is a crucial component in the neural network, which introduces the non-linearity in the network. An activation ...
  • Learning content curation and enrichment 
    V, Venktesh; Mohania, Mukesh (Advisor); Goyal, Vikram (Advisor) (IIIT-Delhi, 2023-03)
    Education in traditional classroom settings was restricted to static content in textbooks. It also assumes all the learners have a similar pace of learning. Online learning platforms have shifted the paradigm and have made ...
  • Analysing long egocentric videos 
    Nagar, Pravin; Arora, Chetan (Advisor) (IIIT-Delhi, 2023-02)
    Egocentric videos are recorded in a hands-free, always-on, under enhanced privacy-sensitive scenario and are often collected from day to weeks. For efficient consumption, such videos require robust video analysis techniques ...
  • Regularized ensemble correlation filter tracking 
    Jain, Monika; Subramanyam, A V (Advisor) (IIIT-Delhi, 2022-06)
    Correlation Filter based visual trackers have demonstrated tremendous progress in object tracking. These trackers primarily use hierarchical features learned from multiple layers of a deep network. However, issues related ...