International Institute of Information Technology, Hyderabad

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).

Digitizing a million books: challenges for document analysis

Abstract: This paper describes the challenges for document image analysis community for building large digital libraries with diverse document categories. The challenges are identified from the experience of the on-going activities toward digitizing and archiving one million books. Smooth workflow has been established for archiving large quantity of books, with the help of efficient image processing algorithms. However, much more research is needed to address the challenges arising out of the diversity of the content in digital libraries.

Region-based active learning for efficient labeling in semantic segmentation

Abstract: As vision-based autonomous systems, such as self-driving vehicles, become a reality, there is an increasing need for large annotated datasets for developing solutions to vision tasks. One important task that has seen significant interest in recent years is semantic segmentation. However, the cost of annotating every pixel for semantic segmentation is immense, and can be prohibitive in scaling to various settings and locations. In this paper, we propose a region-based active learning method for efficient labeling in semantic segmentation. Using the proposed active learning strategy, we show that we are able to judiciously select the regions for annotation such that we obtain 93.8% of the baseline performance (when all pixels are labeled) with labeling of 10% of the total number of pixels. Further, we show that this approach can be used to transfer annotations from a model trained on a given dataset (Cityscapes) to a different dataset (Mapillary), thus highlighting its promise and potential.

NAPS update: network analysis of molecular dynamics data and protein-nucleic acid complexes.

Abstract: Network theory is now a method of choice to gain insights in understanding protein structure, folding and function. In combination with molecular dynamics (MD) simulations, it is an invaluable tool with widespread applications such as analyzing subtle conformational changes and flexibility regions in proteins, dynamic correlation analysis across distant regions for allosteric communications, in drug design to reveal alternative binding pockets for drugs, etc. Updated version of NAPS now facilitates network analysis of the complete repertoire of these biomolecules, i.e., proteins, protein-protein/nucleic acid complexes, MD trajectories, and RNA. Various options provided for analysis of MD trajectories include individual network construction and analysis of intermediate time-steps, comparative analysis of these networks, construction and analysis of average network of the ensemble of trajectories and dynamic cross-correlations. For protein-nucleic acid complexes, networks of the whole complex as well as that of the interface can be constructed and analyzed. For analysis of proteins, protein-protein complexes and MD trajectories, network construction based on inter-residue interaction energies with realistic edge-weights obtained from standard force fields is provided to capture the atomistic details. Updated version of NAPS also provides improved visualization features, interactive plots and bulk execution. URL: http://bioinf.iiit.ac.in/NAPS/.

Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach

Abstract: Drought is one of the major environmental stress conditions affecting the yield of rice across the globe. Unraveling the functional roles of the drought-responsive genes and their underlying molecular mechanisms will provide important leads to improve the yield of rice. Co-expression relationships derived from condition-dependent gene expression data is an effective way to identify the functional associations between genes that are part of the same biological process and may be under similar transcriptional control. For this purpose, vast amount of freely available transcriptomic data can be used for functional annotation. In this study we consider gene expression data for different tissues and developmental stages in response to drought stress. We analyze the network of co-expressed genes to identify drought-responsive genes modules in a tissue and stage-specific manner based on differential expression and gene enrichment analysis. Taking cues from the systems-level behavior of these modules, we propose two approaches to identify clusters of tightly co-expressed/co-regulated genes. Using graph-centrality measures and differential gene expression, we identify biologically informative genes that lack any functional annotation. We show that using orthologous information from other plant species, the conserved co-expression patterns of the uncharacterized genes can be identified. Presence of a conserved neighborhood enables us to extrapolate functional annotation. Alternatively, we show that ‘guide-gene’ approach can help in understanding the tissue-specific transcriptional regulation of uncharacterized genes. Finally, we confirm the predicted roles of uncharacterized genes by the analysis of conserved cis-elements and explain the possible roles of these genes towards drought tolerance

Design of a new CP-ABE with constant-size secret keys for lightweight devices using elliptic curve cryptography

Abstract: The energy cost of public-key cryptography is a vital component of modern secure communications. It inhibits the widespread adoption within the ultra-low energy regimes for example, implantable medical devices and Radio Frequency Identification tags. In the ciphertext-policy attribute-based encryption CP-ABE, an encryptor can decide the access policy that who can decrypt the data. Thus, data will be protected from the unauthorized users. However, most of the existing CP-ABE schemes require huge storage and computational overheads. Moreover, CP-ABE schemes based on bilinear map loose high efficiency over the elliptic curve cryptography because of the requirement of the security parameters of larger size. These drawbacks prevent the use of ultra-low energy devices in practice. In this paper, we aim to propose a novel expressive AND gate access structured CP-ABE scheme with constant-size secret keys CSSK with cost-efficient solutions for encryption and decryption using elliptic curve cryptography, called the CP-ABE-CSSK scheme. In the proposed CP-ABE-CSSK, the size of the secret key is as small as 320 bits. In addition, elliptic curve cryptography is efficient and more suitable for lightweight devices as compared with bilinear pairing-based cryptosystem. Thus, the proposed CP-ABE-CSSK scheme provides low computation and storage overheads with an expressive AND gate access structure as compared with related existing schemes. Consequently, our scheme becomes very practical for CP-ABE key storage and computation cost for ultra-low energy devices. Copyright © 2016 John Wiley & Sons, Ltd.