Browsing E-print Articles by Title

Browsing E-print Articles by Title

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  • 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 ...
  • Raman, Shanmuganathan; Sheth, Kshiteej (Cornell University Library, 2016-09)
  • Hanindriyo, Adie Tri; Yadav, Amit Kumar Singh; Ichibha, Tom; Maezono, Ryo; Nakano, Kousuke; Hongo, Kenta (Cornell University Library, 2020-10)
    The disiloxane molecule is a prime example of silicate compounds containing the Si-O-Si bridge, which is of great interest within the field of quantum chemistry, due to the difficulty in theoretically predicting its ...
  • 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 ...
  • Joshi, Sharad; Korus, Pawel; Khanna, Nitin; Memon, Nasir (Cornell University Library, 2020-04)
    We assess the variability of PRNU-based camera fingerprints with mismatched imaging pipelines (e.g., different camera ISP or digital darkroom software). We show that camera fingerprints exhibit non-negligible variations ...
  • 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 ...
  • 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, ...
  • Gohil, Varun; Walia, Sumit; Mekie, Joycee; Awasthi, Manu (Cornell University Library, 2021-04)
    Today, almost all computer systems use IEEE-754 floating point to represent real numbers. Recently, posit was proposed as an alternative to IEEE-754 floating point as it has better accuracy and a larger dynamic range. The ...
  • Vora, Aditya; Raman, Shanmuganathan (Cornell University Library, 2017-06)
    Segmenting foreground object from a video is a challenging task because of the large deformations of the objects, occlusions, and background clutter. In this paper, we propose a frame-by-frame but computationally efficient ...
  • B, Ramkumar; Hegde, Ravi S.; Laber, Rob; Bojinov, Hristo (Cornell University Library, 2017-06)
  • Raipurkar, Prarabdh; Pal, Rohil; Raman, Shanmuganathan (Cornell University Library, 2021-10)
    The prime goal of digital imaging techniques is to reproduce the realistic appearance of a scene. Low Dynamic Range (LDR) cameras are incapable of representing the wide dynamic range of the real-world scene. The captured ...
  • Donda, Krupali D.; Hegde, Ravi S. (Cornell University Library, 2017-04)
  • Singh, Sarabjeet; Surana, Neelam; Jain, Pranjali; Mekie, Joycee; Awasthi, Manu (Cornell University Library, 2021-10)
    In this paper, we propose a 'full-stack' solution to designing high capacity and low latency on-chip cache hierarchies by starting at the circuit level of the hardware design stack. First, we propose a novel Gain Cell (GC) ...
  • Yadav, Shweta; Chauhan, Jainish; Sain, Joy Prakash; Thirunarayan, Krishnaprasad; Sheth, Amit; Schumm, Jeremiah (Cornell University Library, 2020-11)
    Existing studies on using social media for deriving mental health status of users focus on the depression detection task. However, for case management and referral to psychiatrists, healthcare workers require practical and ...
  • Tewari, Atal; Prateek, Chennuri; Khanna, Nitin (Cornell University Library, 2021-10)
    Rapid technological advancements have tremendously increased the data acquisition capabilities of remote sensing satellites. However, the data utilization efficiency in satellite missions is very low. This growing data ...
  • Vora, Aditya; Raman, Shanmuganathan (Cornell University Library, 2017-06)
    This paper addresses the problem of unsupervised object localization in an image. Unlike previous supervised and weakly supervised algorithms that require bounding box or image level annotations for training classifiers ...
  • Purohit, Palak; Modi, Poojan; Vyas, Udit (Cornell University Library, 2021-09)
    The Segway is a popular self-balancing two-wheeled vehicle. In this paper, we present a control mechanism for the planar Segway problem. The open-loop analysis validates the fact that the system is unstable by default and ...
  • Venkatesh, Praveen; Shah, Viraj; Shah, Vrutik; Kamble, Yash; Mekie, Joycee (Cornell University Library, 2021-11)
    This paper proposes a novel framework for autonomous drone navigation through a cluttered environment. Control policies are learnt in a low-level environment during training and are applied to a complex environment during ...
  • 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 ...
  • Venkatesh, Praveen; Rana, Rwik; Jain, Varun (Cornell University Library, 2021-06)
    In self driving car applications, there is a requirement to predict the location of the lane given an input RGB front facing image. In this paper, we propose an architecture that allows us to increase the speed and robustness ...

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