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Browsing Computer Science and Engineering by Author "Vatsa, Mayank (Advisor)"

Browsing Computer Science and Engineering by Author "Vatsa, Mayank (Advisor)"

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  • Agarwal, Mallika; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) (2017-04-18)
    Recognizing people with their face has received a lot of attention from the research community. However, face recognition for newborns is in a nascent stage. The need for effective identification of newborns has been rising ...
  • Basak, Protichi; De, Saurabh; Vatsa, Mayank (Advisor) (2017-04-18)
    The idea of fusing multiple biometric modalities for the identification of an individual has received significant attention in the last two decades. However, this has been limited to recognizing adults only. With the quality ...
  • Kalra, Harshvardhan; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) (IIIT-Delhi, 2018-07-06)
    Current face recognition systems make extensive use of class-wise disparate features drawn from faces in order to achieve state-of-the-art performances. However, there exists a multitude of information in a given image ...
  • Agrawal, Praful; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) (2014-05-19)
    With the advent of research, it has been established that many leading diseases among women, such as breast cancer, cervical cancer, and autoimmune diseases, can be prevented if diagnosed at initial stage. This research ...
  • Keswani, Sumit; Singh, Richa (Advisor); Vatsa, Mayank (Advisor) (2017-04)
    In past few years, cross-modal information retrieval has drawn much attention due to significant growth in the multimodal data. It takes one type of data as the query to retrieve relevant data of multiple modalities. For ...
  • Gupta, Nikita; Gupta, Sanchit; Singh, Richa (Advisor); Vatsa, Mayank (Advisor) (2017-04-24)
    One of the challenging applications in face recognition is video surveillance, where unconstrained low-resolution video data is captured both in day and night time (visible and near-infrared) with multiple subjects in ...
  • Bhatt, Himanshu S; Singh, Richa (Advisor); Vatsa, Mayank (Advisor) (2014-04-14)
    A covariate in face recognition can be defined as an effect that independently increases the intra-class variability or decreases the inter-class variability or both. Covariates such as pose, illumination, expression, ...
  • Verma, Priyanka; Singh, Richa (Advisor); Vatsa, Mayank (Advisor) (2015-12-03)
    Research in face and gender recognition under constrained environment has achieved an acceptable level of performance. There have been advancements in face and gender recognition in unconstrained environment, however, ...
  • Shah, Mahek; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) (2015-12-05)
    With increasing security concerns, surveillance cameras are playing an important role in the society and face recognition in crowd is gaining more importance than ever. For video face recognition, researchers have primarily ...
  • Jain, Arushi; Singh, Richa (Advisor); Vatsa, Mayank (Advisor) (2017-04-18)
    Face Recognition involves a wide range of applications, many of which are centered around forensic applications. Dead bodies in large-scale calamities like foods and earthquakes require to be identified. However, the bodies ...
  • Agrawal, Navin; Singh, Richa (Advisor); Vatsa, Mayank (Advisor) (2016-09-13)
    Gender classification is used in applications as a soft feature or attribute in biometrics to help identify people. Using gender classification as an indexing technique can boost the performance of facial-biometric. If the ...
  • Bharadwaj, Samarth; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) (2015-09-02)
    Large scale biometric identification systems still lack the versatility to handle challenging situations such as adverse imaging conditions, missing or corrupt data, and non-conventional operating scenarios. It is well ...
  • Sankaran, Anush; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) (IIIT-Delhi, 2017-02)
    Fingerprint recognition has evolved over the decades, providing innumerable applications for improving the modern day security. Based on the method of capture, fingerprints can be classified into four variants: inked, ...
  • Yadav, Shivangi; Vatsa, Mayank (Advisor) (2016-09-13)
    Face recognition is an important area of research due to its requirement in our day-to-day life, be it surveillance or authentication. Current advancements in technology and computational power have shown promising results ...
  • Dhamecha, Tejas Indulal; Singh, Richa (Advisor); Vatsa, Mayank (Advisor) (IIIT-Delhi, 2017-07)
    Due to the unconstrained nature of data capture and non-cooperative subjects, automatic face recognition is still a research challenge for application scenarios such as law enforcement. We observe that challenges of face ...
  • Chowdhury, Anurag; Vatsa, Mayank (Advisor) (2016-09-20)
    Biometric analysis of surveillance videos carries inherent challenges in form of variations in pose, distance, illumination and expression. To address these variations, different methodologies are proposed, including ...
  • Goswami, Gaurav; Singh, Richa (Advisor); Vatsa, Mayank (Advisor) (IIIT-Delhi, 2018-11)
    Automatic face recognition in unconstrained environments is a popular and challenging research problem. With the improvements in recognition algorithms, focus has shifted from addressing various covariates individually to ...

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