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Institution

International Institute of Information Technology, Hyderabad

EducationHyderabad, India
About: International Institute of Information Technology, Hyderabad is a education organization based out in Hyderabad, India. It is known for research contribution in the topics: Computer science & Authentication. The organization has 2048 authors who have published 3677 publications receiving 45319 citations. The organization is also known as: IIIT Hyderabad & International Institute of Information Technology (IIIT).


Papers
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Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors proposed an inception-based deep network architecture called PIG-Net, which effectively characterizes the local and global geometric details of the point clouds.

17 citations

Proceedings Article
01 Jan 2018
TL;DR: In this paper, an auto-encoder based architecture is proposed for phase retrieval under both low overlap, where traditional techniques completely fail, and at higher levels of overlap, and for the high overlap case, optimizing the generator for reducing the forward model error is an appropriate choice.
Abstract: Fourier Ptychography is a recently proposed imaging technique that yields high-resolution images by computationally transcending the diffraction blur of an optical system. At the crux of this method is the phase retrieval algorithm, which is used for computationally stitching together low-resolution images taken under varying illumination angles of a coherent light source. However, the traditional iterative phase retrieval technique relies heavily on the initialization and also need a good amount of overlap in the Fourier domain for the successively captured low-resolution images, thus increasing the acquisition time and data. We show that an auto-encoder based architecture can be adaptively trained for phase retrieval under both low overlap, where traditional techniques completely fail, and at higher levels of overlap. For the low overlap case we show that a supervised deep learning technique using an autoencoder generator is a good choice for solving the Fourier ptychography problem. And for the high overlap case, we show that optimizing the generator for reducing the forward model error is an appropriate choice. Using simulations for the challenging case of uncorrelated phase and amplitude, we show that our method outperforms many of the previously proposed Fourier ptychography phase retrieval techniques.

17 citations

Posted Content
TL;DR: In this paper, a coded caching scheme using line graphs of bipartite graphs in conjunction with projective geometries over finite fields was presented, which achieves a lower subpacketization (albeit possessing a higher rate).
Abstract: Coded Caching is a promising solution to reduce the peak traffic in broadcast networks by prefetching the popular content close to end users and using coded transmissions. One of the chief issues of most coded caching schemes in literature is the issue of large $\textit{subpacketization}$, i.e., they require each file to be divided into a large number of subfiles. In this work, we present a coded caching scheme using line graphs of bipartite graphs in conjunction with projective geometries over finite fields. The presented scheme achieves a rate $\Theta(\frac{K}{\log_q{K}})$ ($K$ being the number of users, $q$ is some prime power) with $\textit{subexponential}$ subpacketization $q^{O((\log_q{K})^2)}$ when cached fraction is upper bounded by a constant ($\frac{M}{N}\leq \frac{1}{q^\alpha}$) for some positive integer $\alpha$). Compared to earlier schemes, the presented scheme has a lower subpacketization (albeit possessing a higher rate). We also present a new subpacketization dependent lower bound on the rate for caching schemes in which each subfile is cached in the same number of users. Compared to the previously known bounds, this bound seems to perform better for a range of parameters of the caching system.

17 citations

Proceedings Article
01 May 2012
TL;DR: Overall, some of the changes of the PDTB scheme render the annotation task much more difficult for the annotators, as also reflected in lower inter-annotator agreement for the relevant sub-tasks.
Abstract: We describe our experiments on evaluating recently proposed modifications to the discourse relation annotation scheme of the Penn Discourse Treebank (PDTB), in the context of annotating discourse relations in Hindi Discourse Relation Bank (HDRB). While the proposed modifications were driven by the desire to introduce greater conceptual clarity in the PDTB scheme and to facilitate better annotation quality, our findings indicate that overall, some of the changes render the annotation task much more difficult for the annotators, as also reflected in lower inter-annotator agreement for the relevant sub-tasks. Our study emphasizes the importance of best practices in annotation task design and guidelines, given that a major goal of an annotation effort should be to achieve maximally high agreement between annotators. Based on our study, we suggest modifications to the current version of the HDRB, to be incorporated in our future annotation work.

17 citations

Proceedings ArticleDOI
15 Mar 2010
TL;DR: This paper would discuss how to handle issues in building multilingual screen reader in Indian languages, including availability of Text-to-Speech (TTS) system, support for reading glyph based font encoded text, and Text Normalization for converting non standard words into standard words.
Abstract: Screen reader is a form of assistive technology to help visually impaired people to use or access the computer and Internet. So far, it has remained expensive and within the domain of English (and some foreign) language computing. For Indian languages this development is limited by: availability of Text-to-Speech (TTS) system in Indian languages, support for reading glyph based font encoded text, Text Normalization for converting non standard words into standard words, supporting multiple languages. In this paper we would discuss how to handle these issues in building multilingual screen reader in Indian languages.

17 citations


Authors

Showing all 2066 results

NameH-indexPapersCitations
Ravi Shankar6667219326
Joakim Nivre6129517203
Aravind K. Joshi5924916417
Ashok Kumar Das562789166
Malcolm F. White5517210762
B. Yegnanarayana5434012861
Ram Bilas Pachori481828140
C. V. Jawahar454799582
Saurabh Garg402066738
Himanshu Thapliyal362013992
Monika Sharma362384412
Ponnurangam Kumaraguru332696849
Abhijit Mitra332407795
Ramanathan Sowdhamini332564458
Helmut Schiessel321173527
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202310
202229
2021373
2020440
2019367
2018364