scispace - formally typeset
Search or ask a question
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: Authentication & Internet security. 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
More filters
Journal ArticleDOI
TL;DR: In this article, the interaction of proline with gold cluster was studied using density functional theory (DFT) using two types of mixed basis sets UB3LYP/6-311++G ∪ LANL2MB and uB3lyp/6 -311++g ∪LANL2DZ were used for optimization of complex structures.
Abstract: Interaction of proline with gold cluster was studied using density functional theory (DFT). Two types of mixed basis sets UB3LYP/6-311++G ∪ LANL2MB and UB3LYP/6-311++G ∪ LANL2DZ were used for optimization of complex structures. Proline interacts with gold cluster either through one anchor bond, N–Au or an anchor bond O–Au associated with a non-conventional O–H...Au hydrogen bond. Among these interactions, higher tendency for interaction is seen with Au cluster through amide terminal. Natural bond orbital analysis (NBO) is used to substantiate the results.

34 citations

Book ChapterDOI
01 Apr 2010
TL;DR: This paper exploits the notion of “item-to-pattern difference” and proposes multiple minsup based FP-growth-like approach to efficiently discover rare association rules and experimental results show that the proposed approach is efficient.
Abstract: Rare association rule is an association rule consisting of rare items. It is difficult to mine rare association rules with a single minimum support (minsup) constraint because low minsup can result in generating too many rules in which some of them can be uninteresting. In the literature, minimum constraint model using “multiple minsup framework” was proposed to efficiently discover rare association rules. However, that model still extracts uninteresting rules if the items’ frequencies in a dataset vary widely. In this paper, we exploit the notion of “item-to-pattern difference” and propose multiple minsup based FP-growth-like approach to efficiently discover rare association rules. Experimental results show that the proposed approach is efficient.

34 citations

Journal ArticleDOI
TL;DR: Some emerging trends of wearable devices are presented followed by a discussion of the main security and functionality requirements along with the threats to the wearable communication environment and a review of some of the recently proposed lightweight authentication protocols for wearable devices based on performance metrics such as computation cost and communication cost.

34 citations

Book ChapterDOI
13 Dec 2006
TL;DR: A document segmentation algorithm that can handle the complexity of Indian scripts in large document image collections by being posed as a graph cut problem that incorporates the apriori information from script structure in the objective function of the cut.
Abstract: Most of the state-of-the-art segmentation algorithms are designed to handle complex document layouts and backgrounds, while assuming a simple script structure such as in Roman script. They perform poorly when used with Indian languages, where the components are not strictly collinear. In this paper, we propose a document segmentation algorithm that can handle the complexity of Indian scripts in large document image collections. Segmentation is posed as a graph cut problem that incorporates the apriori information from script structure in the objective function of the cut. We show that this information can be learned automatically and be adapted within a collection of documents (a book) and across collections to achieve accurate segmentation. We show the results on Indian language documents in Telugu script. The approach is also applicable to other languages with complex scripts such as Bangla, Kannada, Malayalam, and Urdu.

34 citations

Proceedings ArticleDOI
26 May 2015
TL;DR: A framework which performs perception using monocular camera and generates minimum time collision free trajectory and control for any commercial quadcopter flying through cluttered unknown environment is described.
Abstract: Autonomous navigation of generic monocular quadcopter in the natural environment requires sophisticated mechanism for perception, planning and control In this work, we have described a framework which performs perception using monocular camera and generates minimum time collision free trajectory and control for any commercial quadcopter flying through cluttered unknown environment The proposed framework first utilizes supervised learning approach to estimate the dense depth map for video stream obtained from frontal monocular camera This depth map is initially transformed into Ego Dynamic Space and subsequently, is used for computing locally traversable way-points utilizing binary integer programming methodology Finally, trajectory planning and control module employs a convex programming technique to generate collision-free trajectory which follows these way-points and produces appropriate control inputs for the quadcopter These control inputs are computed from the generated trajectory in each update Hence, they are applicable to achieve closed-loop control similar to model predictive controller We have demonstrated the applicability of our system in controlled indoors and in unstructured natural outdoors environment

34 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
Network Information
Related Institutions (5)
Microsoft
86.9K papers, 4.1M citations

90% related

Facebook
10.9K papers, 570.1K citations

89% related

Google
39.8K papers, 2.1M citations

89% related

Carnegie Mellon University
104.3K papers, 5.9M citations

87% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202310
202229
2021373
2020440
2019367
2018364