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000826414 019__ $$a1024169841$$a1026199075$$a1029061643$$a1030291594
000826414 020__ $$a9783319717678$$q(electronic book)
000826414 020__ $$a3319717677$$q(electronic book)
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000826414 0247_ $$a10.1007/978-3-319-71767-8$$2doi
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000826414 049__ $$aISEA
000826414 050_4 $$aTA1634
000826414 08204 $$a006.37$$223
000826414 24500 $$aComputational vision and bio inspired computing /$$cD. Jude Hemanth, S. Smys, editors.
000826414 264_1 $$aCham, Switzerland :$$bSpringer,$$c[2018]
000826414 300__ $$a1 online resource :$$billustrations.
000826414 336__ $$atext$$btxt$$2rdacontent
000826414 337__ $$acomputer$$bc$$2rdamedia
000826414 338__ $$aonline resource$$bcr$$2rdacarrier
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000826414 4901_ $$aLecture notes in computational vision and biomechanics,$$x2212-9413 ;$$vvolume 28
000826414 504__ $$aIncludes bibliographical references and index.
000826414 5050_ $$aIntro; Contents; Genetic Algorithm Based Hybrid Attribute Selection Using Customized Fitness Function; Abstract; 1 Introduction; 2 Proposed Hybrid Approach to Attribute Selection; 2.1 Attribute Selection; 2.2 Information Gain Based Entropy; 2.3 Genetic Algorithm; 2.3.1 Methodology; 2.3.2 Modifications in Fitness Function; 2.4 Proposed Hybrid Approach; 3 Results and Discussion; 3.1 Dataset Description; 3.2 Parameter Settings; 3.3 Experimental Results; 4 Conclusion; References; Application of Evolutionary Particle Swarm Optimization Algorithm in Test Suite Prioritization; Abstract
000826414 5058_ $$a1 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
000826414 5058_ $$a2 Literature Survey3 Proposed Work; 3.1 Architecture for Trust Enhanced CIF; 3.2 Data Quality Assurance; 3.3 Trust Modeling for Trust Enhanced CIF; 3.3.1 Trust Metrics; 3.3.2 CSP Trust Score; 4 Simulation and Results of Trust Enhanced CIF; 5 Conclusion; References; Combined Classifier Approach for Offline Handwritten Devanagari Character Recognition Using Multiple Features; Abstract; 1 Introduction; 1.1 About Devanagari Script; 1.2 Related Work; 2 Proposed Approach; 2.1 Preprocessing; 2.2 Feature Extraction; 2.3 Classifier; 3 Experimental Results; 4 Conclusion; References
000826414 5058_ $$aComprehensive 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
000826414 5058_ $$a4 Simulation Analysis5 Conclusion; References; Securing Image Posts in Social Networking Sites; Abstract; 1 Introduction; 2 Motivation; 3 Literature Survey; 3.1 Image Security Techniques; 3.2 Recommender Systems; 3.3 Summary of Findings; 4 Proposed Work; 5 Evaluation Based Selection of Security Technique; 5.1 Algorithm 1: Perfect Secrecy Algorithm; 5.2 Selection of Peers; 6 Trust Calculation and Recommendation; 6.1 Reliability of the Peer; 6.2 Credibility of the Peer; 6.3 Trust Value of the User; 6.4 Recommender Engine; 7 Experimental Setup and Results; 8 Conclusion; References
000826414 506__ $$aAccess limited to authorized users.
000826414 520__ $$aThis is the proceedings of the International Conference On Computational Vision and Bio Inspired Computing (ICCVBIC 2017) held at RVS Technical Campus, September 21-22, 2017. It includes papers on state of the art innovations in bio-inspired computing applications, where new algorithms and results are produced and described. Additionally, this volume addresses evolutionary computation paradigms, artificial neural networks and biocomputing. It focuses mainly on research based on visual interference on the basis of biological images. Computation of data sources also plays a major role in routine day-to-day life for the purposes such as video transmission, wireless applications, fingerprint recognition and processing, big data intelligence, automation, human centric recognition systems. With the advantage of processing bio-inspired computations, a variety of computational paradigms can be processed. Finally, this book also treats the formation of neural networks by enabling local connectivity within it with the aid of vision sensing elements. The work also provides potential directions for future research. .
000826414 588__ $$aOnline resource; title from PDF title page (viewed February 26, 2018).
000826414 650_0 $$aComputer vision.
000826414 7001_ $$aHemanth, D. Jude,$$eeditor.
000826414 7001_ $$aSmys, S.,$$eeditor.
000826414 77608 $$iPrint version: $$z3319717669$$z9783319717661$$w(OCoLC)1007925436
000826414 830_0 $$aLecture notes in computational vision and biomechanics ;$$vv. 28.
000826414 852__ $$bebk
000826414 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-71767-8$$zOnline Access$$91397441.1
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