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Title Computational vision and bio inspired computing / D. Jude Hemanth, S. Smys, editors
Published Cham, Switzerland : Springer, [2018]
Online access available from:
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Description 1 online resource : illustrations (some color)
Series Lecture notes in computational vision and biomechanics, 2212-9413 ; volume 28
Lecture notes in computational vision and biomechanics ; v. 28
Contents Intro; Contents; Genetic Algorithm Based Hybrid Attribute Selection Using Customized Fitness Function; Abstract; 1 Introduction; 2 Proposed Hybrid Approach to Attribute Selection; 2.1 Attribute Selection; 2.2 Information Gain Based Entropy; 2.3 Genetic Algorithm; 2.3.1 Methodology; 2.3.2 Modifications in Fitness Function; 2.4 Proposed Hybrid Approach; 3 Results and Discussion; 3.1 Dataset Description; 3.2 Parameter Settings; 3.3 Experimental Results; 4 Conclusion; References; Application of Evolutionary Particle Swarm Optimization Algorithm in Test Suite Prioritization; Abstract
1 Introduction2 Related Work; 3 Test Case Prioritization; 3.1 Prioritizing Based on Statement Coverage; 3.2 Prioritizing Based on Branch Coverage; 4 Particle Swarm Optimization; 4.1 Mapping PSO to Test Suite Prioritization; 4.2 Fitness Calculation in PSO; 4.3 Proposed Algorithm; 4.4 Flow Chart of Proposed Algorithm; 5 Analysis and Evaluation; 5.1 Data Collection; 5.2 Case Study: Calculator; 5.3 Empirical Results; 6 Results and Interpretation; 7 Threats to Validity; 8 Conclusion and Future Work; References; An Autonomous Trust Model for Cloud Integrated Framework; Abstract; 1 Introduction
2 Literature Survey3 Proposed Work; 3.1 Architecture for Trust Enhanced CIF; 3.2 Data Quality Assurance; 3.3 Trust Modeling for Trust Enhanced CIF; 3.3.1 Trust Metrics; 3.3.2 CSP Trust Score; 4 Simulation and Results of Trust Enhanced CIF; 5 Conclusion; References; Combined Classifier Approach for Offline Handwritten Devanagari Character Recognition Using Multiple Features; Abstract; 1 Introduction; 1.1 About Devanagari Script; 1.2 Related Work; 2 Proposed Approach; 2.1 Preprocessing; 2.2 Feature Extraction; 2.3 Classifier; 3 Experimental Results; 4 Conclusion; References
4 Simulation Analysis5 Conclusion; References; Securing Image Posts in Social Networking Sites; Abstract; 1 Introduction; 2 Motivation; 3 Literature Survey; 3.1 Image Security Techniques; 3.2 Recommender Systems; 3.3 Summary of Findings; 4 Proposed Work; 5 Evaluation Based Selection of Security Technique; 5.1 Algorithm 1: Perfect Secrecy Algorithm; 5.2 Selection of Peers; 6 Trust Calculation and Recommendation; 6.1 Reliability of the Peer; 6.2 Credibility of the Peer; 6.3 Trust Value of the User; 6.4 Recommender Engine; 7 Experimental Setup and Results; 8 Conclusion; References
Comprehensive Study on Usage of Multi Objectives in Recommender SystemsAbstract; 1 Introduction; 2 Objectives of Recommendations; 2.1 User Preference; 2.2 Prediction Accuracy; 2.3 Novelty; 2.4 Serendipity; 2.5 Diversity; 2.6 Trust; 3 Literature Survey; 3.1 Approaches Dealing with Combined Objectives; 3.2 Context Awareness; 3.3 Personalization; 3.4 Evolutionary Algorithms; 4 Evaluation of Recommender Systems; 5 Discussion and Conclusion; References; Visual Analysis of Genetic Algorithms While Solving 0-1 Knapsack Problem; Abstract; 1 Introduction; 2 Related Works; 3 Design of Experiments
Summary This is the proceedings of the International Conference On Computational Vision and Bio Inspired Computing (ICCVBIC 2017) held at RVS Technical Campus, September 21-22, 2017. It includes papers on state of the art innovations in bio-inspired computing applications, where new algorithms and results are produced and described. Additionally, this volume addresses evolutionary computation paradigms, artificial neural networks and biocomputing. It focuses mainly on research based on visual interference on the basis of biological images. Computation of data sources also plays a major role in routine day-to-day life for the purposes such as video transmission, wireless applications, fingerprint recognition and processing, big data intelligence, automation, human centric recognition systems. With the advantage of processing bio-inspired computations, a variety of computational paradigms can be processed. Finally, this book also treats the formation of neural networks by enabling local connectivity within it with the aid of vision sensing elements. The work also provides potential directions for future research
Bibliography Includes bibliographical references and index
Notes Online resource; title from PDF title page (EBSCO, viewed February 26, 2018)
Subject Computer vision.
Form Electronic book
Author Hemanth, D. Jude, editor
Smys, S., editor
ISBN 3319717677 (electronic bk.)
9783319717678 (electronic bk.)