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    Learning Across Domains: Applications to Text-based Person Search and Multi-Source Domain Adaptation 

    Aggarwal, Surbhi
    With rapid development in technology and ubiquitous presence of diverse types of sensors, a large amount of data from different modalities (e.g., text, audio, images etc.) describing the same person/ object/event has ...

    Deep Learning in Computer Vision: Studies in Neuro-image Segmentation and Satellite Image Super-resolution 

    Roy, Shreya
    Single image super-resolution (SR) has been a topic of great interest in the computer vision and deep learning community and has found applications in many areas including quality enhancement of satellite images. As the ...

    Self-Supervised Domain Adaptation Frameworks for Computer Vision Tasks 

    Kundu, Jogendra Nath
    There is a strong incentive to build intelligent machines that can understand and adapt to changes in the visual world without human supervision. While humans and animals learn to perceive the world on their own, almost ...

    Landmark Estimation and Image Synthesis Guidance using Self-Supervised Networks 

    Karmali, Tejan
    The exponential rise in the availability of data over the past decade has fuelled research in deep learning. While supervised deep learning models achieve near-human performance using annotated data, it comes with an ...

    Learning to Perceive Humans From Appearance and Pose 

    Seth, Siddharth
    Analyzing humans and their activities takes a central role in computer vision. This requires machine learning models to encapsulate both the diverse poses and appearances exhibited by humans. Estimating the 3D poses of ...

    Advances in High Dynamic Range Imaging Using Deep Learning 

    Ram Prabhakar, Kathirvel
    Natural scenes have a wide range of brightness, from dark starry nights to bright sunlit beaches. Our human eyes can perceive such a vast range of illumination through various adaptation techniques, thus allowing us to ...

    Novel Deep Learning Methods for Improving Low-Dose Computed Tomography Perfusion Imaging of Brain 

    Dutta, Arindam
    Computed Tomography (CT) Perfusion imaging is a non-invasive medical imaging modality that has also established itself as a fast and economical imaging modality for diagnosing cerebrovascular diseases such as acute ischemia, ...

    A study on Deep Learning Approaches, Architectures and Training Methods for Crowd Analysis 

    Sam, Deepak Babu
    Analyzing large crowds quickly is one of the highly sought-after capabilities nowadays. Especially in terms of public security and planning, this assumes prime importance. But automated reasoning of crowd images or videos ...

    Development of Novel Deep Learning Models with Improved Generalizability for Medical Image Analysis 

    Naveen, P
    Medical imaging is a process of visualization of disease/tissue in a non-invasive manner. Several imaging techniques like computed tomography (CT), magnetic resonance imaging (MRI), optical coherence tomography (OCT), and ...

    Deep Learning for Hand-drawn Sketches: Analysis, Synthesis and Cognitive Process Models 

    Sarvadevabhatla, Ravi Kiran
    Deep Learning-based object category understanding is an important and active area of research in Computer Vision. Most work in this area has predominantly focused on the portion of depiction spectrum consisting of ...
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    AuthorAddepalli, Sravanti (1)Aggarwal, Surbhi (1)Dutta, Arindam (1)Karmali, Tejan (1)Kundu, Jogendra Nath (1)Narayanan, Ramanujam (1)Naveen, P (1)Nayak, Gaurav Kumar (1)Ram Prabhakar, Kathirvel (1)Roy, Shreya (1)... View MoreSubject
    Deep Learning (13)
    TECHNOLOGY (11)Computer Vision (6)Convolutional Neural Network (3)3D Human Pose Estimation (2)Adversarial Robustness (2)Domain Adaptation (2)Self-Supervised Learning (2)Absence of training data (1)AdaDepth (1)... View MoreHas File(s)Yes (13)

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