Year-2020

 

Recent Submissions

  • Bhattacharyya, Pramit; Mutharaju, V. Raghava (advisor) (2020-07)
    Building an ontology is not only a time-consuming process, but it is also confusing, especially for beginners and the inexperienced. Although ontology developers can take the help of domain experts in building an ontology, ...
  • Gola, Nikhil; Goyal, Vikram (advisor) (IIIT-Delhi, 2020-06)
    Traffic speed prediction is one of the challenging task and has many applications. Existing solutions either use crowd-sourced data or sophisticated technologies to perform the task, and hence are costly and unreliable. ...
  • Srivastava, Abhishek; Shah, Rajiv Ratn (advisor); Yu, Yi (advisor) (IIIT-Delhi, 2020-07)
    Automating the process of melody generation from lyrics has been a challenging research task in the field of artificial intelligence. Lately, however, music-related datasets have become available at large-scale, and with ...
  • Gupta, Neha; Prakash, Naveen (advisor) (IIIT-Delhi, 2020-05)
    Conventional data warehouse systems are implemented either on a multi-dimensional database or a relational database. While the earlier supports MOLAP operations, the other supports ROLAP operations. In this work, we used ...
  • Yasvi, Maleeha Arif; Mutharaju, V. Raghava (advisor) (IIIT-Delhi, 2020-07)
    Ontologies evolve over time due to changes in the domain and the requirements of the application. Maintaining an ontology over time and keeping it up-to-date with respect to the changes in the domain and the requirements ...
  • 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 ...
  • Srivastava, Kshitij; Biyani, Pravesh (advisor) (IIIT-Delhi, 2020-06)
    The concept of open data has become quite popular in recent times among governments and public-facing organizations promoting transparency and collaboration. In a similar expedition, the Open Transit Data Platform for Delhi ...
  • Sundriyal, Divyanshu; Vatsa, Mayank (advisor); Singh, Richa (advisor) (IIIT-Delhi, 2020-06)
    Deep learning systems require a large amount of labelled training dataset. However large amount of labelled data is not available in many cases as it requires considerable human effort to label each sample correctly. In ...
  • Yadav, Khushbu; Purandare, Rahul (advisor) (IIIT-Delhi, 2020-08)
    Java being designed in a flexible and user-friendly demeanour, makes it the most accepted programming language for the development of web applications and platforms. Due to the immense popularity, there comes the responsibility ...
  • Sundriyal, Himanshu; Vatsa, Mayank (advisor); Singh, Richa (advisor) (IIIT-Delhi, 2020-06)
    Identifying face attributes is an ongoing problem of research which is used in bio-metrics, surveillance etc. In past, researchers have proposed methods which predict single facial attribute at a time. Real-time applications ...
  • Saxena, Garvita; Singh, Pushpendra (advisor) (IIIT-Delhi, 2020)
    Most sensor based mobile phone applications like navigation systems, pothole detection, pedometers, traffic detection, etc. rely on the strict and stable positioning of the mobile phone at a particular place throughout ...
  • Tyagi, Arjun; Subramanyam, A.V. (advisor) (IIIT-Delhi, 2020-08)
    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 ...
  • Makkar, Sakshi; Chakraborty, Tanmoy (advisor) (IIIT-Delhi, 2020-07)
    Online hate speech, particularly over microblogging platforms like Twitter, has emerged as arguably the most severe issue of the past decade. Several countries have reported a steep rise in hate crimes infuriated by ...
  • Dey, Alvin; Chakroborty, Tanmoy (advisor) (IIIT-Delhi, 2020-06)
    Multi-document summarization (MDS) is the task of reflecting key points from any set of documents into a concise text paragraph. In the past, it has been used to aggregate news, tweets, product reviews, etc. from various ...