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  • Automatic content aware non-photorealistic rendering of images 
    Patil, Akshay Gadi; Raman, Shanmuganathan (Cornell University Library, 2016-04)
    Non-photorealistic rendering techniques work on image features and often manipulate a set of characteristics such as edges and texture to achieve a desired depiction of the scene. Most computational photography methods ...
  • Automatic segmentation of dynamic objects from an image pair 
    Malireddi, Sri Raghu; Raman, Shanmuganathan (Cornell University Library, 2016-04)
    Automatic segmentation of objects from a single image is a challenging problem which generally requires training on large number of images. We consider the problem of automatically segmenting only the dynamic objects from ...
  • Band-to-band tunneling based ultra-energy efficient silicon neuron 
    Chavan, Tanmay; Dutta, Sangya; Mohapatra, Nihar Ranjan; Ganguly, Udayan (Cornell University Library, 2019-02)
    The human brain comprises about a hundred billion neurons connected through quadrillion synapses. Spiking Neural Networks (SNNs) take inspiration from the brain to model complex cognitive and learning tasks. Neuromorphic ...
  • Block-level double JPEG compression detection for image forgery localization 
    Verma, Vinay; Singh, Deepak; Khanna, Nitin (Cornell University Library, 2020-03)
  • Dataset augmentation with synthetic images improves semantic segmentation 
    Rajpura, Param; Goyal, Manik; Hegde, Ravi S.; Bojinov, Hristo (Cornell University Library, 2017-09)
    Although Deep Convolutional Neural Networks trained with strong pixel-level annotations have significantly pushed the performance in semantic segmentation, annotation efforts required for the creation of training data ...
  • Efficient image retargeting for high dynamic range scenes 
    Salvi, Govind; Sharma, Puneet; Raman, Shanmuganathan (Cornell University Library, 2013-05)
    Most of the real world scenes have a very high dynamic range (HDR). The mobile phone cameras and the digital cameras available in markets are limited in their capability in both the range and spatial resolution. Same ...
  • Exploring temporal differences in 3D convolutional neural networks 
    Kanojia, Gagan; Kumawat, Sudhakar; Raman, Shanmuganathan (Cornell University Library, 2019-09)
    Traditional 3D convolutions are computationally expensive, memory intensive, and due to large number of parameters, they often tend to overfit. On the other hand, 2D CNNs are less computationally expensive and less memory ...
  • First steps toward CNN based source classification of document images shared over messaging app 
    Joshi, Sharad; Saxena, Suraj; Khanna, Nitin (Cornell University Library, 2018-08)
    Knowledge of source smartphone corresponding to a document image can be helpful in a variety of applications including copyright infringement, ownership attribution, leak identification and usage restriction. In this letter, ...
  • Multi-level encoder-decoder architectures for image restoration 
    Mastan, Indra Deep; Raman, Shanmuganathan (Cornell University Library, 2019-05)
    Many real-world solutions for image restoration are learning-free and based on handcrafted image priors such as self-similarity. Recently, deep-learning methods that use training data have achieved state-of-the-art results ...
  • Source printer classification using printer specific local texture descriptor 
    Joshi, Sharad; Khanna, Nitin (Cornell University Library, 2018-06)
    The knowledge of source printer can help in printed text document authentication, copyright ownership, and provide important clues about the author of a fraudulent document along with his/her potential means and motives. ...
  • SymmSLIC: symmetry aware superpixel segmentation and its applications 
    Nagar, Rajendra; Raman, Shanmuganathan (Cornell University Library, 2018-05)
    Over-segmentation of an image into superpixels has become a useful tool for solving various problems in image processing and computer vision. Reflection symmetry is quite prevalent in both natural and man-made objects and ...
  • Zero shot hashing 
    Raman, Shanmuganathan; Pachori, Shubham (Cornell University Library, 2016-10)
    This paper provides a framework to hash images containing instances of unknown object classes. In many object recognition problems, we might have access to huge amount of data. It may so happen that even this huge data ...

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