Blar i forfatter "Horsch, Ludwig Alexander"

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    • Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts 

      Agarwal, Rohit; Prasad, Dilip Kumar; Horsch, Ludwig Alexander; Gupta, Deepak Kumar (Journal article; Tidsskriftartikkel; Peer reviewed, 2023)
      Many real-world applications based on online learning produce streaming data that is haphazard in nature, i.e., contains missing features, features becoming obsolete in time, the appearance of new features at later points in time and a lack of clarity on the total number of input features. These challenges make it hard to build a learnable system for such applications, and almost no work exists in ...

    • Guided U-Net Aided Efficient Image Data Storing with Shape Preservation 

      Banerjee, Nirwan; Malakar, Samir; Gupta, Deepak Kumar; Horsch, Ludwig Alexander; Prasad, Dilip Kumar (Chapter; Bokkapittel, 2023-11-02)
      The proliferation of high-content microscopes ( 32 GB for a single image) and the increasing amount of image data generated daily have created a pressing need for compact storage solutions. Not only is the storage of such massive image data cumbersome, but it also requires a significant amount of storage and data bandwidth for transmission. To address this issue, we present a novel deep learning ...

    • Mabnet: Master Assistant Buddy Network With Hybrid Learning for Image Retrieval 

      Agarwal, Rohit; Das, Gyanendra; Aggarwal, Saksham; Horsch, Ludwig Alexander; Prasad, Dilip Kumar (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-05-05)
      Image retrieval has garnered a growing interest in recent times. The current approaches are either supervised or self-supervised. These methods do not exploit the benefits of hybrid learning using both supervision and self-supervision. We present a novel Master Assistant Buddy Network (MAB-Net) for image retrieval which incorporates both the learning mechanisms. MABNet consists of master and assistant ...