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  • 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 ...
  • Unsupervised domain adaptation for semantic segmentation 
    Singhal, Ojus; Anand, Saket (Advisor); Agarwal, Sharat (Advisor) (IIIT-Delhi, 2023-11-27)
    Unsupervised domain adaptation (UDA) has emerged as a vital research area in the field of machine learning and computer vision. It addresses the challenge of adapting models trained on a labeled source domain to perform ...
  • Unsupervised learning of low rank subspace projection using graph embedding 
    Jain, Kshitiz; Priysha; Subramanyam, A V (Advisor) (IIIT-Delhi, 2020-05-28)
    Subspace learning has often been explored for various applications such as dimensionality reduction, denoising, clustering and feature extraction among others. However, low rank subspace learning for clustering as well ...
  • Unsupervised meta generative object re-identification 
    Giri, Biman; Subramanyam, A V (Advisor) (IIIT-Delhi, 2022-05)
    Unsupervised domain adaptation severely suffers from huge domain gap in fine grained recognition tasks such as vehicle re-identification (re-id). Existing works either focus on fully unsupervised methods using tracklet or ...
  • Unsupervised pre-trained vitals signals embeddings for fine-tuned prognostication: a multi resolution approach 
    Sheoran, Ashwin; Patil, Vedant; Sethi, Tavpritesh (Advisor) (IIIT-Delhi, 2023-11-29)
    The project introduces an innovative method for predicting shock in ICU patients by leveraging unsupervised pre-trained embeddings from vital signs. Utilizing the extensive eICU and MIMIC datasets, the research focuses on ...
  • Unsupervised pre-trained vitals signals embeddings for fine-tuned prognostication: a multi-resolution approach 
    Sheoran, Ashwin; Patil, Vedant; Sethi, Tavpritesh (Advisor) (IIIT-Delhi, 2023-11-29)
    The project introduces an innovative method for predicting shock in ICU patients by leveraging unsupervised pre-trained embeddings from vital signs. Utilizing the extensive eICU and MIMIC datasets, the research focuses on ...
  • UP-Hist Tree : efficient data structure for high utility pattern mining from transaction databases 
    Goyal, Vikram; Dawar, Siddharth (2015-02-11)
    High-utility itemset mining is an emerging research area in the field of Data Mining. Several algorithms were proposed to find high- utility itemsets from transaction databases and use a data structure called UP-tree ...
  • Upper and lower bounds of various centrality measures on planar and sparse graphs 
    Bhattacharya, Sudatta; Bera, Debajyoti (Advisor) (IIIT-Delhi, 2020-08-03)
    In this thesis we address the problem of computing closeness centrality, Harmonic centrality and a few related centrality measures that operate on the shortest paths in a graph. We consider sparse graphs, especially ...
  • Use of smartphone's microphone sensor to estimate rate of respiration 
    Phokela, Kanchanjot Kaur; Naik, Vinayak (Advisor) (2017-07)
    Sleep plays a crucial part of one’s physical and mental wellbeing. Polysomnography, which is the gold standard for measuring and analyzing sleep requires the subject to sleep overnight with many expensive sensors attached ...
  • User identities across social networks: quantifying linkability and nudging users to control linkability 
    Chandok, Srishti; Kumaraguru, Ponnurangam (Advisor) (2017)
    The Online Social Network (OSN) landscape has transformed significantly over the past few years with the emergence of networks. The primary capabilities of these online networks differ. Few of the major leading ones are: ...
  • User identity linkage : data collection, dataset biases, method, control and application 
    Kaushal, Rishabh; Kumaraguru, Ponnurangam (Advisor) (IIIT-Delhi, 2020-10)
    Online Social Networks (OSNs) have become popular platforms for online users. Users typically register and maintain their accounts (user identities) across different OSNs to share a variety of content and remain connected ...
  • User interest and influence mining in location-based social networks 
    Likhyani, Ankita; Bedathur, Srikanta (Advisor) (IIIT-Delhi, 2022-01)
    Over the past decade with the explosion of smartphones and pervasive usage of data connectivity, location-based services have increasingly become popular. As a result, Location- based Social Network(LBSN) such as Foursquare, ...
  • User mobility-aware device-to-device and aerial communication networks 
    Peer, Mansi; Bohara, Vivek Ashok (Advisor); Srivastava, Anand (Advisor) (IIIT-Delhi, 2022-04)
    Due to the enormous number of cellular users, the traffic load on the core network is increasing rapidly. Hence, it is difficult to maintain the required quality of service in the cellular network. Further, the normal ...
  • User-centric power optimization in smart home environments 
    Gupta, Saurabh; Buduru, Arun Balaji (Advisor); Kumaraguru, Ponnurangam (Advisor) (IIIT-Delhi, 2022-07)
    Rapid advancements in the Internet of Things (IoT) have facilitated efficient de- ployments of smart environment solutions for specific user requirements. With the increase in the number of IoT devices, it has become ...
  • Using reinforcement learning for multimodal sarcasm explanation 
    Goel, Palaash; Akhtar, Md. Shad (Advisor) (IIIT-Delhi, 2023-11-29)
    Multimodal sarcasm explanation is a challenging natural language understanding task that deals with training machines to understand the semantic incongruence present in sarcasm as a form of communication and resolve it to ...
  • Using smartphone-based accelerometer to detect travel by metro train 
    Vij, Megha; Naik, Vinayak (Advisor); Gunturi, Venkata M. Viswanath (Advisor) (2016-07-18)
    We look at the problem of using accelerometer in smartphones to detect whether the user is at a metro train station or in a metro train. Currently, we have solutions to detect simple activities, such as sitting or walking. ...
  • Using twitter sentiments and search volumes index to predict oil, gold, forex and markets indices 
    Rao, Tushar; Srivastava, Saket (2012-03-26)
    Behavioral finance is an upcoming research field which is drawing a lot of attention of both academia and industry. With changing dynamics of internet behavior of millions across the globe, it provides opportunity to ...
  • Using XR for augmenting abilities 
    Lakra, Aneesha; Bhayana, Rachit; Parnami, Aman (Advisor) (IIIT-Delhi, 2021-12)
    Colocated experiences among strangers open a door to opportunities to allow meaningful experiences shared by people who have never met before. These experiences are complex in their approach, aim, and involvement of ...
  • USRP based through wall radar 
    Goyal, Sangeeta; Ram, Shobha Sundar (Advisor); Bohara, Vivek Ashok (Advisor) (2016-09)
    Radar systems for detecting the humans present behind the wall are powerful tools for law enforcement, military and elderly care. Walls are complex propagation mediums that introduce attenuation, refraction and multipath ...
  • Utility and privacy guarantees of differential privacy 
    Srivastava, Shubham; Bera, Debajyoti (Advisor) (2016-09-15)
    The primary aim of any survey is to facilitate analysis of sensitive data to extract useful information, without jeopardizing privacy of the participants. Privacy models like k-anonymity do not guarantee privacy against ...

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