Institutional Repository

This Repository has created and designed to collect, preserve and disseminate the scholarly intellectual output of Indraprastha Institute of Information Technology - Delhi (IIIT-Delhi). Repositories are important tools for preserving an organization's legacy; they facilitate digital preservation and scholarly communication.

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Recently Added

  • Compressed sensing based underwater acoustic channel estimation using two dimensional frequency characterization 
    Ansari, Naushad; Gupta, Anubha (Advisor) (IIIT-Delhi, 2016)
    Underwater acoustic (UWA) channel estimation in shallow water depths is a challenging problem due to rapidly fluctuating transients in the acoustic channel impulse response. Transmitted signal undergoes nonstationary ...
  • Latent factor models for collaborative filtering 
    Gogna, Anuprriya; Majumdar, Angshul (Advisor) (IIIT-Delhi, 2017)
    The enormous growth in online availability of information content has made Recommender Systems (RS) an integral part of most online portals and e-commerce sites. Most websites and service portals, be it movie rental services, ...
  • Sparse recovery techniques for hyperspectral imaging 
    Aggarwal, Hemant Kumar; Majumdar, Angshul (Advisor) (2016-12-23)
    Human vision is a powerful imaging system that can capture and interpret light energy coming from different sources although it is limited to visible light. There are various applications such as face recognition, medical ...
  • Cognitive spectrum sharing protocols for energy harvesting wireless sensor nodes 
    Peer, Mansi; Bohara, Vivek Ashok (Advisor) (2016-12-06)
    Energy consumption is one of the primary concerns in the deployment of futuristic wireless sensor networks. On one hand due to advent of technologies such as Internet of Things (IoT), there has been tremendous growth in ...
  • Regularized autoencoders 
    Gupta, Kavya; Majumdar, Angshul (Advisor) (2016-11-09)
    Autoencoders are Neural Networks trained in order to map input to its output. Autoencoders are designed to enable the network to copy input to output as close as possible. Following this, the network will be able to learn ...

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