Search Results for author: Sumohana S. Channappayya

Found 6 papers, 2 papers with code

Can Perceptual Guidance Lead to Semantically Explainable Adversarial Perturbations?

no code implementations24 Jun 2021 P Charantej Reddy, Aditya Siripuram, Sumohana S. Channappayya

In this work, we attempt to understand the mechanics by systematically answering the following question: do imperceptible adversarial perturbations focus on changing the regions of the image that are important for classification?

SSIM

Deep No-reference Tone Mapped Image Quality Assessment

no code implementations8 Feb 2020 Chandra Sekhar Ravuri, Rajesh Sureddi, Sathya Veera Reddy Dendi, Shanmuganathan Raman, Sumohana S. Channappayya

The novelty of this work is its ability to visualize various distortions as quality maps (distortion maps), especially in the no-reference setting, and to use these maps as features to estimate the quality score of tone mapped images.

Image Quality Assessment Tone Mapping

Quality Aware Generative Adversarial Networks

1 code implementation NeurIPS 2019 Parimala Kancharla, Sumohana S. Channappayya

Generative Adversarial Networks (GANs) have become a very popular tool for implicitly learning high-dimensional probability distributions.

Image Generation No-Reference Image Quality Assessment +1

Optical Character Recognition (OCR) for Telugu: Database, Algorithm and Application

no code implementations20 Nov 2017 Chandra Prakash Konkimalla, Manikanta Srikar Yellapragada, Trishal Gayam, Souraj Mandal, Sumohana S. Channappayya

To address the challenge of OCR for Telugu, we make three contributions in this work: (i) a database of Telugu characters, (ii) a deep learning based OCR algorithm, and (iii) a client server solution for the online deployment of the algorithm.

Optical Character Recognition Optical Character Recognition (OCR) +1

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