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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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Book ChapterDOI
10 Sep 2010
TL;DR: This paper presents a hybrid implementation of sparse bundle adjustment on the GPU using CUDA, with the CPU working in parallel, achieving a speedup of 30-40 times over the standard CPU implementation for datasets with upto 500 images on an Nvidia Tesla C2050 GPU.
Abstract: Large-scale 3D reconstruction has received a lot of attention recently. Bundle adjustment is a key component of the reconstruction pipeline and often its slowest and most computational resource intensive. It hasn't been parallelized effectively so far. In this paper, we present a hybrid implementation of sparse bundle adjustment on the GPU using CUDA, with the CPU working in parallel. The algorithm is decomposed into smaller steps, each of which is scheduled on the GPU or the CPU. We develop efficient kernels for the steps and make use of existing libraries for several steps. Our implementation outperforms the CPU implementation significantly, achieving a speedup of 30-40 times over the standard CPU implementation for datasets with upto 500 images on an Nvidia Tesla C2050 GPU.

38 citations

Proceedings ArticleDOI
01 Sep 2019
TL;DR: Graphical Object Detection ( GOD) as discussed by the authors uses transfer learning and domain adaptation to handle the scarcity of labeled training images for graphical object detection task in the document images and achieves promising results as compared to state-of-the-art techniques.
Abstract: Graphical elements: particularly tables and figures contain a visual summary of the most valuable information contained in a document. Therefore, localization of such graphical objects in the document images is the initial step to understand the content of such graphical objects or document images. In this paper, we present a novel end-to-end trainable deep learning based framework to localize graphical objects in the document images called as Graphical Object Detection ( GOD ). Our framework is data-driven and does not require any heuristics or meta-data to locate graphical objects in the document images. The GOD explores the concept of transfer learning and domain adaptation to handle scarcity of labeled training images for graphical object detection task in the document images. Performance analysis carried out on the various public benchmark data sets: ICDAR -2013, ICDAR - POD2017 and UNLV shows that our model yields promising results as compared to state-of-the-art techniques.

37 citations

Journal ArticleDOI
01 Aug 2020
TL;DR: This paper presents a secure fine-grained user access control scheme for data usage in the IoT environment, which supports multi-authority ABE and it is highly scalable as both the ABE key size stored in the user’s smart card and ciphertext size needed for authentication request are constant with respect to the number of attributes.
Abstract: With the ever-increasing rate of adoption of internet-enabled smart devices, the allure of greater integration of technologies, such as smart home, smart city, and smart grid into everyday life is undeniable. However, this trend inevitably leaves a massive amount of information and infrastructure connected to the public Internet, which exposes the data to many security threats and challenges. In this paper, we discuss the need for fine-grained user access control for IoT smart devices. The inherently distributed nature of IoT environment necessitates the support of multi-authority attribute-based encryption (ABE) for the implementation of fine-grained access control. Therefore, we present a secure fine-grained user access control scheme for data usage in the IoT environment. The proposed scheme is a three-factor user access control scheme, which supports multi-authority ABE and it is highly scalable as both the ABE key size stored in the user’s smart card and ciphertext size needed for authentication request are constant with respect to the number of attributes. Through the formal and informal security analysis, we show that the proposed scheme is secure and robust against several potential attacks required in an IoT environment. Moreover, we demonstrate that the proposed scheme performs at par or better than existing schemes while providing greater functionality features.

37 citations

Proceedings Article
01 Jan 2008
TL;DR: A more discerning method which applies different techniques based on the word origin in transliteration, which does not require training data on the target side, while it uses more sophisticated techniques on the source side.
Abstract: Transliteration is the process of transcribing words from a source script to a target script. These words can be content words or proper nouns. They may be of local or foreign origin. In this paper we present a more discerning method which applies different techniques based on the word origin. The techniques used also take into account the properties of the scripts. Our approach does not require training data on the target side, while it uses more sophisticated techniques on the source side. Fuzzy string matching is used to compensate for lack of training on the target side. We have evaluated on two Indian languages and have achieved substantially better results (increase of up to 0.44 in MRR) than the baseline and comparable to the state of the art. Our experiments clearly show that word origin is an important factor in achieving higher accuracy in transliteration.

37 citations

Journal ArticleDOI
TL;DR: This paper investigates the possibility of using GA optimization methods in the theoretical design of laser pulses to bring about quantum state transitions in molecules to choose only a small limited number of parameters to vary and to choose these parameters so that they correspond to those available to the experimentalist.
Abstract: Conventionally optimal control theory has been used in the theoretical design of laser pulses through the direct variation in the electric field of the laser pulse as a function of time. This often leads to designed laser pulses which contain a broad and seemingly arbitrary frequency structure that varies in time in a manner which may be difficult to realize experimentally. In contrast, the experimental design of laser pulses has used a genetic algorithm (GA) approach, varying only those laser parameters actually available to the experimentalist. We investigate in this paper the possibility of using GA optimization methods in the theoretical design of laser pulses to bring about quantum state transitions in molecules. This allows us to select only a small limited number of parameters to vary and to choose these parameters so that they correspond to those available to the experimentalist. In the paper we apply our methods to the vibrational-rotational excitation of the HF molecule. We choose a small limited number of frequencies and vary only the associated electric field amplitudes and pulse envelopes. We show that laser pulses designed in this way can lead to very high transition probabilities.

37 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