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  • Gangopadhyay, Aalok; Singh, Prajwal; Raman, Shanmuganathan (Cornell University Library, 2021-01)
    Automatic extraction of raw data from 2D line plot images is a problem of great importance having many real-world applications. Several algorithms have been proposed for solving this problem. However, these algorithms ...
  • 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 ...
  • 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, ...
  • Kanojia, Gagan; Raman, Shanmuganathan (Cornell University Library, 2020-10)
    Consider a set of n images of a scene with dynamic objects captured with a static or a handheld camera. Let the temporal order in which these images are captured be unknown. There can be n! possibilities for the temporal ...
  • 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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