001445478 000__ 10526cam\a2200649Ii\4500
001445478 001__ 1445478
001445478 003__ OCoLC
001445478 005__ 20230310003833.0
001445478 006__ m\\\\\o\\d\\\\\\\\
001445478 007__ cr\cn\nnnunnun
001445478 008__ 220326s2022\\\\si\a\\\\o\\\\\101\0\eng\d
001445478 020__ $$a9789811912535$$q(electronic bk.)
001445478 020__ $$a981191253X$$q(electronic bk.)
001445478 020__ $$z9789811912528
001445478 0247_ $$a10.1007/978-981-19-1253-5$$2doi
001445478 035__ $$aSP(OCoLC)1306063135
001445478 040__ $$aEBLCP$$beng$$erda$$epn$$cEBLCP$$dGW5XE$$dOCLCO$$dOCLCF$$dSFB$$dOCLCQ
001445478 049__ $$aISEA
001445478 050_4 $$aQ335$$b.I58 2021eb
001445478 08204 $$a006.3/82$$223
001445478 1112_ $$aInternational Conference on Bio-inspired Computing, Theories and Applications$$n(16th :$$d2021 :$$cTaiyuan, China)
001445478 24510 $$aBio-inspired computing :$$b16th international conference, BIC-TA 2021, Taiyuan, China, December 17-19, 2021 : revised selected papers.$$nPart II /$$cLinqiang Pan, Zhihua Cui, Jianghui Cai, Lianghao Li (eds.).
001445478 24630 $$aBIC-TA 2021
001445478 264_1 $$aSingapore :$$bSpringer,$$c[2022]
001445478 264_4 $$c©2022
001445478 300__ $$a1 online resource (448 pages) :$$billustrations (chiefly color).
001445478 336__ $$atext$$btxt$$2rdacontent
001445478 337__ $$acomputer$$bc$$2rdamedia
001445478 338__ $$aonline resource$$bcr$$2rdacarrier
001445478 4901_ $$aCommunications in computer and information science ;$$v1566
001445478 500__ $$aInternational conference proceedings.
001445478 500__ $$aIncludes author index.
001445478 5050_ $$aIntro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Machine Learning and Computer Vision -- Point Clouds Registration Algorithm Based on Spatial Structure Similarity of Visual Keypoints -- 1 Introduction -- 2 Method -- 2.1 2D Visual Keypoints -- 2.2 Depth Completion and Back-Project -- 2.3 Screening 3D Keypoints -- 2.4 Rigid Transformation Parameter Estimation -- 3 Experiment -- 3.1 Data and Metrics -- 3.2 Experiment and Comparison -- 4 Conclusion -- References -- Software Defect Prediction Based on SMOTE-Tomek and XGBoost -- 1 Introduction -- 2 Related Work -- 2.1 Sampling Technique -- 2.2 Cost-Sensitive Learning -- 2.3 Ensample Learning Algorithm -- 3 The Proposed Model -- 3.1 SMOTE-Tomek -- 3.2 XGBoost -- 3.3 STX Model -- 4 Experiments -- 4.1 Datasets -- 4.2 Performance Measures -- 4.3 Results and Discussion -- 4.4 Statistical Comparison of Software Defect Predictors -- 5 Conclusion -- References -- Imbalance Classification Based on Deep Learning and Fuzzy Support Vector Machine -- 1 Introduction -- 2 Related Work -- 2.1 Data-Level -- 2.2 Algorithm-Level -- 3 Proposed Method -- 3.1 Feature Extraction with Deep Learning -- 3.2 Random Feature Oversampling Based on Center Distance -- 3.3 Fuzzy Support Vector Machine -- 4 Experiments and Results -- 4.1 Evaluation Metrics and Datasets -- 4.2 Experiment Settings -- 4.3 Results and Analysis -- 5 Conclusion -- References -- Community Detection Based on Surrogate Network -- 1 Introduction -- 2 Preliminaries -- 2.1 Spectral Clustering -- 2.2 EA-Based Community Detection -- 3 Proposed Method -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Experimental Results and Discussions -- 5 Conclusions -- References -- Fault-Tolerant Scheme of Cloud Task Allocation Based on Deep Reinforcement Learning -- 1 Introduction -- 2 Related Works -- 3 Cloud System and Fault Model.
001445478 5058_ $$a3.1 Task Model -- 3.2 Fault Model -- 3.3 APSDQN MDP Model -- 4 APSDQN Implementation -- 5 Simulation Experiment -- 5.1 Experimental Setup -- 5.2 Experimental Results and Analysis -- 6 Conclusion -- References -- Attention-Guided Memory Model for Video Object Segmentation -- 1 Introduction -- 2 Related work -- 3 Methodology -- 3.1 Network Overview -- 3.2 Joint Attention Guider -- 3.3 Spatial-Temporal Feature Fusion -- 3.4 Implementation of Other Modules -- 3.5 Network Training -- 4 Experiments -- 4.1 Comparision to State-of-the-Art -- 4.2 Ablation Study -- 5 Conclusion -- References -- Multi-workflow Scheduling Based on Implicit Information Transmission in Cloud Computing Environment -- 1 Introduction -- 2 Workflow Schedule Model -- 2.1 Workflow Model -- 2.2 Problem Expression -- 3 Multifactorial Evolutionary Algorithm for DAG Schedule -- 3.1 MFEA Based on Combinatorial Population (CP-MFEA) -- 3.2 Generation of Population -- 3.3 Generation of Offspring -- 3.4 Evaluate Offspring -- 4 Experiment and Discuss -- 4.1 Basic Workflow Structure -- 4.2 Experimental Setup -- 4.3 Results and Analysis -- 5 Conclusion -- References -- Pose Estimation Based on Snake Model and Inverse Perspective Transform for Elliptical Ring Monocular Vision -- 1 Introduction -- 2 Ellipse Ring Contour Extraction Based on Snake Model -- 2.1 Rough Contour Extraction -- 2.2 Refined Contour Extraction -- 3 Ellipse Correction Based on Inverse Perspective Transformation -- 3.1 Solving Inverse Perspective Transformation Matrix -- 3.2 Ellipse Correction and Pose Estimation -- 4 Experimental Results and Analysis -- 5 Conclusion -- References -- Enhancing Aspect-Based Sentiment Classification with Local Semantic Information -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Methodology -- 4.1 Embedding and Bidirectional LSTM -- 4.2 Obtaining Semantic Information.
001445478 5058_ $$a4.3 FMDG: Obtaining Local Semantic Information -- 4.4 Information Fusion -- 4.5 Sentiment Classification -- 4.6 Training -- 5 Experiments -- 5.1 Dataset and Experiment Setup -- 5.2 Models for Comparison -- 5.3 Overall Result -- 5.4 Ablation Study -- 6 Conclusion -- References -- A Chinese Dataset Building Method Based on Data Hierarchy and Balance Analysis in Knowledge Graph Completion -- 1 Introduction -- 2 Problem Analysis -- 2.1 Existence of Meaningless Triples -- 2.2 Unbalanced Data Volume -- 3 Methods -- 3.1 Use Indicators to Measure Dataset Structure -- 3.2 Method of Constructing Chinese Dataset -- 3.3 Knowledge Graph Completion Model Selection -- 4 Experiments -- 5 Conclusions -- References -- A Method for Formation Control of Autonomous Underwater Vehicle Formation Navigation Based on Consistency -- 1 Introduction -- 2 AUV Formation System Description -- 2.1 Graph Theory -- 2.2 Kinematic Model -- 2.3 Information Interaction Model -- 3 Formation Control Algorithm Design -- 3.1 Definition of Covariate -- 3.2 Second-Order Consistency Control Algorithm -- 3.3 Model Predictive Control Rate Design -- 4 Simulation Research -- 4.1 Simulation Setup -- 4.2 Simulation Results and Analysis -- 5 Conclusion -- References -- A Formation Control Method of AUV Group Combining Consensus Theory and Leader-Follower Method Under Communication Delay -- 1 Introduction -- 2 Preliminaries and Modelling -- 2.1 Graph Theory -- 2.2 AUV Model -- 2.3 Communication Modelling -- 3 Consistency Control Algorithm Based on Leader-Following Method for AUV Group -- 3.1 Consistency Control Algorithm Without Communication Delay -- 3.2 Consistency Control Algorithm with Communication Delay -- 4 Simulation Results -- 4.1 Simulation of Consistency Control Algorithm Without Communication Delay -- 4.2 Simulation of Consistency Control Algorithm with Communication Delay -- 5 Conclusion.
001445478 5058_ $$a4.2 Simulation of Heterogeneous AUV Cluster Consistency Algorithm with Time Delay Under Event Trigger Control -- 5 Conclusion -- References -- Edge Computing Energy-Efficient Resource Scheduling Based on Deep Reinforcement Learning and Imitation Learning -- 1 Introduction -- 2 Related Works -- 3 Scheduling System -- 3.1 Workload Processor -- 3.2 Problem Definition -- 3.3 Environment Model -- 4 Simulation Experiment -- 5 Conclusion -- References -- Metric Learning with Distillation for Overcoming Catastrophic Forgetting -- 1 Introduction -- 2 Related Work -- 2.1 Incremental Learning -- 2.2 Metric Learning -- 2.3 Knowledge Distillation -- 3 Proposed Method -- 3.1 Network Structure and its Losses -- 3.2 Knowledge Distillation Embedded in the Network -- 3.3 Classifier -- 4 Experiment -- 4.1 Datasets -- 4.2 Implementation Details -- 4.3 Ablation Experiment -- 4.4 Comparison Methods -- 5 Conclusions -- References -- Feature Enhanced and Context Inference Network for Pancreas Segmentation -- 1 Introduction -- 2 Related Work -- 2.1 Deep Learning Methods -- 2.2 Attention Mechanism -- 3 Methods -- 3.1 Feature Encoder -- 3.2 Feature Space Mapping -- 3.3 Feature Enhancement -- 3.4 Decoder -- 4 Experiment -- 4.1 Experiment Setup -- 4.2 Comparative Experiments -- 4.3 Comparative Experiments -- 5 Discussion and Conclusion -- References -- Object Relations Focused Siamese Network for Remote Sensing Image Change Detection -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Basic Network Architecture -- 3.2 Geo-Objects Relations Module -- 3.3 Feature Enhancement -- 4 Experiment -- 4.1 Experiment Settings -- 4.2 Ablation Experiments -- 4.3 Comparative Experiments -- 5 Conclusion -- References -- MLFF: Multiple Low-Level Features Fusion Model for Retinal Vessel Segmentation -- 1 Introduction -- 2 Related Works -- 3 Multiple Low-Level Feature Fusion Model.
001445478 506__ $$aAccess limited to authorized users.
001445478 520__ $$aThis two-volume set (CCIS 1565 and CCIS 1566) constitutes selected and revised papers from the 16th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2021, held in Taiyuan, China, in December 2021. The 67 papers presented were thoroughly reviewed and selected from 211 submissions. The papers are organized in the following topical sections: evolutionary computation and swarm intelligence; DNA and molecular computing; machine learning and computer vision.
001445478 588__ $$aDescription based upon print version of record.
001445478 650_0 $$aNatural computation$$vCongresses.
001445478 650_6 $$aCalcul naturel$$vCongrès.
001445478 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001445478 655_7 $$aConference papers and proceedings.$$2lcgft
001445478 655_7 $$aActes de congrès.$$2rvmgf
001445478 655_0 $$aElectronic books.
001445478 7001_ $$aPan, Linqiang,$$eeditor.
001445478 7001_ $$aCui, Zhihua,$$eeditor.
001445478 7001_ $$aCai, Jianghui,$$eeditor.
001445478 7001_ $$aLi, Lianghao,$$eeditor.
001445478 77608 $$iPrint version:$$aPan, Linqiang$$tBio-Inspired Computing: Theories and Applications$$dSingapore : Springer Singapore Pte. Limited,c2022$$z9789811912528
001445478 830_0 $$aCommunications in computer and information science ;$$v1566.
001445478 852__ $$bebk
001445478 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-19-1253-5$$zOnline Access$$91397441.1
001445478 909CO $$ooai:library.usi.edu:1445478$$pGLOBAL_SET
001445478 980__ $$aBIB
001445478 980__ $$aEBOOK
001445478 982__ $$aEbook
001445478 983__ $$aOnline
001445478 994__ $$a92$$bISE