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  • Dceiphering the heterogeneity of three-dimensional volumes using cryo-electron microscopy 
    Saini, Chandan; Kumar, Vibhor (Advisor) (IIIT-Delhi, 2023-05)
    The cryo-electron microscopy (cryo-EM) technique captures 2D projections of biological structures, revealing their inherent Heterogeneity arising from structural flexibility, conformational changes, and distinct functional ...
  • A deadline-aware scheduler for smart factory using wifi 6 
    Mishra, Anis; Bhattacharya, Arani (Advisor); Maity, Mukulika (Advisor); Das, Syamantak (Advisor) (IIIT-Delhi, 2023-12-09)
    We discuss the optimization of wireless network scheduling in smart factories, specifically focusing on data packets with varying deadlines and importance levels. The proposed solution involves utilizing IEEE 802.11ax (WiFi ...
  • Decentralized education system - DESy 
    Gupta, Pratham; Mohania, Mukesh (Advisor); Garg, Anuj (Advisor) (IIIT-Delhi, 2022-05)
    Education is now often regarded as the most important contributor to a country’s economic prosperity and stability. Digitalization plays a key part in the development and progress of every area in today’s world. The education ...
  • Decentralized federated learning in wireless networks 
    Sohini, Ayush Madhan; Dominic, Divin; Prasad, Ranjitha (Advisor) (IIIT- Delhi, 2022-12)
    Current wireless applications such as autonomous driving, UAVs, IOT devices, etc. generate massive amounts of data that can be utilized to train machine learning models for decision making. Privacy, security and bandwidth ...
  • Decentralized federated learning in wireless networks 
    Kumari, Pooja; Prasad, Ranjitha (Advisor) (IIIT-Delhi, 2022-12)
    In today’s world, Machine learning and deep learning has changed the vision in CS/IT fields. It is continuously exciting us in different ways, giving us amazing results and solving many problems in different fields. With ...
  • Deciphering genetic bias underlying in global population for lipid homeostasis 
    Garg, Himanshi; Ray, Arjun (Advisor) (IIIT-Delhi, 2023-03)
    Lipid homeostasis refers to the balance of the levels of various lipids, such as fats and cholesterol, within cells and organisms. This balance is crucial for many physiological functions. Disruptions to lipid homeostasis, ...
  • Deciphering the genetic bias underlying in global population for lipid homeostasis 
    Samota, Praveen Singh; Ray, Arjun (Advisor) (IIIT-Delhi, 2023-11-29)
    Maintaining lipid homeostasis, the equilibrium of lipid levels, including fats and cholesterol within cells and organisms, is vital for numerous physiological functions. Disruptions in lipid homeostasis, often spurred by ...
  • Decoding the molecular basis of iterative stress response (ISR) 
    Aggarwal, Anmol; Ahuja, Gaurav (Advisor) (IIIT-Delhi, 2023-09)
    Across evolutionary history, every organism has developed the ability to adapt to fluctuations in environmental conditions, thereby striking a balance between efficient growth and survival. In the case of yeast, when exposed ...
  • 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 ...
  • Deep dictionary learning 
    Tariyal, Snigdha; Majumdar, Angshul (Advisor) (2016-09-13)
    This Thesis focuses on combining the two well researched concepts of representation learning – Dictionary Learning and Deep Learning. These two learning paradigms have been known for long. Ever since, plethora of papers ...
  • Deep dictionary learning 
    Singhal, Vanika; Majumdar, Angshul (Advisor) (IIIT-Delhi, 2019-08)
    Currently there are three basic frameworks in deep learning - stacked autoencoders (SAE), deep belief network (DBN) and convolutional neural network (CNN); SAE and DBN can be applied to arbitrary inputs but CNN can only ...
  • Deep learning approach for face recognition with disguise variations 
    Chawla, Mohit; Singh, Richa (Advisor); Vatsa, Mayank (Advisor) (IIIT-Delhi, 2019-07)
    With the increased interest in face recognition across di erent applications, the research in this area has ourished over the past few decades. However, face recognition with disguise variations has gained little ...
  • Deep learning assisted methods for microscopic blood Cancer imaging analysis 
    Gehlot, Shiv; Gupta, Anubha (Advisor) (IIIT-Delhi, 2022-04-08)
    This thesis, “Deep Learning Assisted Methods for Microscopic Blood Cancer Imaging Analysis” aims to develop deep learning-based CAD tools for Acute Lymphoblastic Leukemia (ALL) and Multiple Myeloma (MM). A CAD tool typically ...
  • Deep learning based 3D reconstruction of indoor scenes 
    Hegde, Srinidhi; Anand, Saket (Advisor); Sharma, Ojaswa (Advisor) (2017-04-18)
    Recent advancement in deep learning techniques has opened doors for wide variety of applications. With growing interests in deep learning and geometry, lots of computer vision problems have been tackled using deep learning. ...
  • Deep learning based multitask learning for first-person videos 
    Gupta, Divam; Arora, Chetan (Advisor) (IIIT-Delhi, 2016-07-18)
    First person videos captured from wearable cameras are growing in popularity.Standard algo- rithms developed for third person videos often do not work for such egocentric videos because of drastic change in camera ...
  • Deep learning for attribute prediction and small sample size problems 
    Sethi, Akshay; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) (IIIT-Delhi, 2018-04-17)
    The first part of this work focuses on facial attribute prediction using a novel deep learning formulation, termed as R-Codean autoencoder. The work presents Cosine similarity based loss function in an autoencoder which ...
  • Deep learning for multimedia application 
    Ahuja, Aditya; Shah, Rajiv Ratn (Advisor) (IIIT-Delhi, 2023-11-29)
    Recent advancements in speech applications prominently feature Deep Learning, driving significant progress in the challenging task of separating speech signals from multi-speaker speech mixtures. Speech Separation models ...
  • Deep learning-based Alzheimer’s disease diagnostics using medical images 
    Seraj, Mohammad; Murugan, N Arul (Advisor); Subramaniyam, A.V. (Advisor) (IIIT-Delhi, 2024-05-01)
    In the ever-evolving landscape of medical innovation, the pursuit of accurate and efficient diagnostic tools for neurodegenerative diseases, notably Alzheimer's, has become increasingly urgent. The relentless progression ...
  • Deep mean shift clustering 
    Madaan, Pulkit; Maiti, Abhishek; Anand, Saket (Advisor); Mittal, Sushil (Advisor) (IIITD-Delhi, 2019-04-15)
    We use Mean Shift clustering in the latent space of an auto-encoder to have a better representation of the data and a more structured latent space. Instead of just using the mode of the distribution calculated using kernel ...
  • Deep mean shift clustering 
    Madaan, Pulkit; Maiti, Abhishek; Anand, Saket (Advisor); Mittal, Sushil (Advisor) (IIIT-Delhi, 2019-11-15)
    We use Mean Shift clustering in the latent space of an auto-encoder to have a better representation of the data and a more structured latent space. Instead of just using the mode of the distribution calculated using kernel ...

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