Advances in Computing Applications

doi:10.1007/978-981-10-2630-0

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Journal Article•DOI•

Retrotransposons in Plant Genomes: Structure, Identification, and Classification through Bioinformatics and Machine Learning.

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Simon Orozco-Arias, Gustavo Isaza¹, Romain Guyot•Institutions (1)

University of Caldas¹

06 Aug 2019-International Journal of Molecular Sciences

TL;DR: Important aspects of TEs are discussed, such as their structure, importance in the evolution and architecture of the host, and their current classifications and nomenclatures, and current methods and their limitations are addressed.

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Abstract: Transposable elements (TEs) are genomic units able to move within the genome of virtually all organisms. Due to their natural repetitive numbers and their high structural diversity, the identification and classification of TEs remain a challenge in sequenced genomes. Although TEs were initially regarded as “junk DNA”, it has been demonstrated that they play key roles in chromosome structures, gene expression, and regulation, as well as adaptation and evolution. A highly reliable annotation of these elements is, therefore, crucial to better understand genome functions and their evolution. To date, much bioinformatics software has been developed to address TE detection and classification processes, but many problematic aspects remain, such as the reliability, precision, and speed of the analyses. Machine learning and deep learning are algorithms that can make automatic predictions and decisions in a wide variety of scientific applications. They have been tested in bioinformatics and, more specifically for TEs, classification with encouraging results. In this review, we will discuss important aspects of TEs, such as their structure, importance in the evolution and architecture of the host, and their current classifications and nomenclatures. We will also address current methods and their limitations in identifying and classifying TEs.

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50 citations

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Journal Article•DOI•

An introduction to biometric recognition

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Anil K. Jain¹, Arun Ross², Salil Prabhakar•Institutions (2)

Michigan State University¹, West Virginia University²

01 Jan 2004-IEEE Transactions on Circuits and Systems for Video Technology

TL;DR: A brief overview of the field of biometrics is given and some of its advantages, disadvantages, strengths, limitations, and related privacy concerns are summarized.

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Abstract: A wide variety of systems requires reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user and no one else. Examples of such applications include secure access to buildings, computer systems, laptops, cellular phones, and ATMs. In the absence of robust personal recognition schemes, these systems are vulnerable to the wiles of an impostor. Biometric recognition, or, simply, biometrics, refers to the automatic recognition of individuals based on their physiological and/or behavioral characteristics. By using biometrics, it is possible to confirm or establish an individual's identity based on "who she is", rather than by "what she possesses" (e.g., an ID card) or "what she remembers" (e.g., a password). We give a brief overview of the field of biometrics and summarize some of its advantages, disadvantages, strengths, limitations, and related privacy concerns.

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4,678 citations

"Advances in Computing Applications" refers background or methods in this paper

...High-Performance SQL [1] explained RBO and CBO level tuning models....
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...In dynamic scenes, shadow detection can be used for change detection, scene matching, understanding relative object position and size [1, 17]....
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...Stream ciphers and re-keying approaches [1] capitalize on these algorithms...
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...The ACM Computing Classification System 2012 is used as knowledgebase for the experiments [1]....
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...,4,2,0,1] [1] [0,1,2,1,1,0,0,0,1,0,0,4,0,0,1,0,....
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Journal Article•DOI•

Information fusion in biometrics

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Arun Ross¹, Anil K. Jain¹•Institutions (1)

Michigan State University¹

01 Sep 2003-Pattern Recognition Letters

TL;DR: This paper addresses the problem of information fusion in biometric verification systems by combining information at the matching score level by combining three biometric modalities (face, fingerprint and hand geometry).

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1,611 citations

"Advances in Computing Applications" refers background or methods in this paper

...from cyberbullying and their communication from explicit messages [13]....
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...companies like SunPartner Technologies, French Technology company Oledcomm are succeeded to develop sensors that both downloads data and charges battery itself using those light rays [13]....
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...(3) Further shadows usually degrade the visual quality of the image leading to serious problems in segmentation and object extraction [13, 22]....
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...marked them for the secure sifting of chat and instant messages [10, 13] which does...
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...Depending on the properties such as position, intensity and edges which the shadow exhibits, the shadows are classified as cast, self or attached [13, 14]....
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Journal Article•DOI•

Multimodal fusion for multimedia analysis: a survey

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Pradeep K. Atrey¹, M. Anwar Hossain², Abdulmotaleb El Saddik², Mohan S. Kankanhalli³•Institutions (3)

University of Winnipeg¹, University of Ottawa², National University of Singapore³

01 Nov 2010-Multimedia Systems

TL;DR: This survey aims at providing multimedia researchers with a state-of-the-art overview of fusion strategies, which are used for combining multiple modalities in order to accomplish various multimedia analysis tasks.

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Abstract: This survey aims at providing multimedia researchers with a state-of-the-art overview of fusion strategies, which are used for combining multiple modalities in order to accomplish various multimedia analysis tasks. The existing literature on multimodal fusion research is presented through several classifications based on the fusion methodology and the level of fusion (feature, decision, and hybrid). The fusion methods are described from the perspective of the basic concept, advantages, weaknesses, and their usage in various analysis tasks as reported in the literature. Moreover, several distinctive issues that influence a multimodal fusion process such as, the use of correlation and independence, confidence level, contextual information, synchronization between different modalities, and the optimal modality selection are also highlighted. Finally, we present the open issues for further research in the area of multimodal fusion.

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1,019 citations

"Advances in Computing Applications" refers background or methods in this paper

...Shadow detection in static images uses the application domain of 3D analysis of object for the purpose of extraction, light source detection, object shape, illumination and occluders’ geometry [2, 10, 17]....
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...In dynamic scenes, shadow detection can be used for change detection, scene matching, understanding relative object position and size [1, 17]....
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...As attocell in indoor navigation has small size so bandwidth reuse is possible which results in high spatial spectral efficiency provided to the users [17]....
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...From this stable set, connectivity values were selected to give multiple intensities with this selected range [15, 17]....
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...Self shadows do not create a problem because the objects’ outer boundaries are clearly detectable, which is the basic requirement of shadow detection [14, 17]....
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Journal Article•DOI•

Integrating faces and fingerprints for personal identification

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Lin Hong¹, Anil K. Jain¹•Institutions (1)

Michigan State University¹

01 Dec 1998-IEEE Transactions on Pattern Analysis and Machine Intelligence

TL;DR: A prototype biometrics system which integrates faces and fingerprints is developed which overcomes the limitations of face recognition systems as well as fingerprint verification systems and operates in the identification mode with an admissible response time.

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Abstract: An automatic personal identification system based solely on fingerprints or faces is often not able to meet the system performance requirements. We have developed a prototype biometrics system which integrates faces and fingerprints. The system overcomes the limitations of face recognition systems as well as fingerprint verification systems. The integrated prototype system operates in the identification mode with an admissible response time. The identity established by the system is more reliable than the identity established by a face recognition system. In addition, the proposed decision fusion scheme enables performance improvement by integrating multiple cues with different confidence measures. Experimental results demonstrate that our system performs very well. It meets the response time as well as the accuracy requirements.

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651 citations

Proceedings Article•DOI•

Combination of multiple classifiers using local accuracy estimates

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K. Woods¹, Kevin W. Bowyer¹, W.P. Kegelmeyer²•Institutions (2)

University of South Florida¹, Sandia National Laboratories²

18 Jun 1996

TL;DR: A method for combining classifiers that use estimates of each individual classifier's local accuracy in small regions of feature space surrounding an unknown test sample that performs better on data from a real problem in mammogram image analysis than do other recently proposed CMC techniques.

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Abstract: Combination of multiple classifiers (CMC) has recently drawn attention as a method of improving classification accuracy. This paper presents a method for combining classifiers that use estimates of each individual classifier's local accuracy in small regions of feature space surrounding an unknown test sample. Only the output of the most locally accurate classifier is considered. We address issues of (1) optimization of individual classifiers, and (2) the effect of varying the sensitivity of the individual classifiers on the CMC algorithm. Our algorithm performs better on data from a real problem in mammogram image analysis than do other recently proposed CMC techniques.

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476 citations

"Advances in Computing Applications" refers background in this paper

...(3) Further shadows usually degrade the visual quality of the image leading to serious problems in segmentation and object extraction [13, 22]....
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...In Li-Fi, each head light and back light can be turned into Li-Fi transmitter developing an intelligent transport system where cars can talk to each other and also to the traffic signal lights and street lights providing the statistics and position of vehicles [22]....
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..., trilateral filter [22], can be analyzed for performance....
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...to semi-honest [22] or semi-honest-but-curious [5] parties which are only partially...
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...The authors of [22] address the problem of scheduling periodic parallel tasks on a multiresource platform with task of real-time constraints....
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Advances in Computing Applications

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"Advances in Computing Applications" refers background or methods in this paper

"Advances in Computing Applications" refers background or methods in this paper

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