LEADER 11828nam a2200481 i 4500001 99129042864106421 005 20231110213101.0 006 m o d | 007 cr cnu|||||||| 008 221113s2022 si a ob 001 0 eng d 020 981-16-9572-5 020 981-16-9573-3 020 981-16-9573-3 035 (MiAaPQ)EBC6943626 035 (Au-PeEL)EBL6943626 035 (CKB)21448757900041 035 (PPN)261520539 035 (EXLCZ)9921448757900041 040 MiAaPQ |beng |erda |epn |cMiAaPQ |dMiAaPQ 050 4 QA76.9.N37 |b.S697 2022 082 0 730 |223 245 00 Computational vision and bio-inspired computing : |bproceedings of ICCVBIC 2021 / |cedited by S. Smys, João Manuel R. S. Tavares, Valentina Emilia Balas. 264 1 Singapore : |bSpringer, |c[2022] 264 4 |c©2022 300 1 online resource (877 pages) 336 text |btxt |2rdacontent 337 computer |bc |2rdamedia 338 online resource |bcr |2rdacarrier 490 1 Advances in Intelligent Systems and Computing ; |vv.1420 505 0 Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- Molecular Docking Analysis of Selected Phytochemicals for the Treatment of Proteus Syndrome -- 1 Introduction -- 2 Methods and Materials -- 3 Results and Discussion -- 4 Conclusion and Future Prospects -- References -- A Deep Learning-Based Detection of Wrinkles on Skin -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Computer Vision -- 3.2 Convolution Neural Network (CNN) -- 3.3 Hough Trnaformer -- 4 Experimental Results -- 5 Conclusion -- References -- Image Transmission Using Leach and Security Using RSA in Wireless Sensor Networks -- 1 Introduction -- 2 Literature Survey -- 3 Leach with RSA: Proposed Scheme -- 4 Simulation Results -- 5 Conclusion -- References -- Code Injection Prevention in Content Management Systems Using Machine Learning -- 1 Introduction -- 2 Background and Related Work -- 3 Our Work -- 3.1 Data Gathering -- 3.2 Data Analysis and Feature Extraction -- 3.3 Dataset -- 3.4 Feature Selection -- 3.5 Machine Learning Using Logistic Regression Algorithm -- 4 Results -- 4.1 Model Interpretation -- 5 Conclusion -- References -- A Review of Hyperspectral Image Classification with Various Segmentation Approaches Based on Labelled Samples -- 1 Introduction -- 1.1 Organization of the Paper -- 2 Datasets and Metrics Used for Hyperspectral Image Classification -- 3 Literature Survey -- 3.1 Machine Learning Techniques -- 3.2 Neural Network Techniques -- 3.3 Analysis Dependent on Various Parameters -- 4 Discussion -- 5 Future Technologies -- 6 Conclusion -- References -- Improvements in User Targeted Offline Advertising Using CNN and Deviation-Based Queue Scheduling -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Overview -- 3.2 Convolutional Neural Network -- 3.3 Deviation-Based Queue Generation -- 4 Results and Discussion. 505 8 5 Performance Comparison -- 5.1 Overlapping Target Audience Problem -- 5.2 Comparison of TARP 2.0 with Random Display and Display Using TARP -- 5.3 Delay Time Comparison of TARP 2.0 with TARP -- 6 Conclusion -- References -- Movie Recommendation System Using Hybrid Collaborative Filtering Model -- 1 Introduction -- 1.1 Literature Survey -- 2 Need and Applicability -- 2.1 Need -- 2.2 Applicability -- 3 Proposed Approach -- 3.1 Dataset Preparation -- 3.2 Dataset Description -- 3.3 Modeling -- 4 Results -- 5 Conclusion -- References -- Hybrid Pipeline Infinity Laplacian Plus Convolutional Stage Applied to Depth Completion -- 1 Introduction -- 1.1 Related Works -- 2 Method -- 2.1 Used Metric -- 2.2 Proposed Metric -- 3 Practical Model Implementation -- 3.1 Convolutional Stage -- 3.2 Convolutional Stage for the Completed Depth Map -- 4 Parameters Estimation -- 4.1 Learning Curve for the Complete Pipeline -- 4.2 Learning Curve for Median-Pipeline -- 4.3 Learning Curve Convolutional Stage-Median-Pipeline Simplified Metric -- 4.4 Learning Curve SC1-Median-Pipeline with Simple Metric -- 5 Experiments and Dataset -- 5.1 Dataset -- 5.2 Experiments -- 6 Results -- 7 Discussion -- 8 Conclusions -- References -- A Novel Approach of DEMOO with SLA Algorithm to Predict Protein Interactions -- 1 Introduction -- 2 Methodology -- 2.1 Feature Extraction -- 2.2 Label Propagation Algorithm -- 2.3 Incremental Depth Extension (INDEX) Approach -- 2.4 Formation of a PPI Network -- 2.5 Neighborhood Topology with Protein Interaction Prediction -- 2.6 Functional Characteristics of Protein Interaction Prediction -- 2.7 Predicting PPIs Using ASA -- 2.8 Differential Evolution Algorithm for Multi-objective Optimization -- 2.9 Stochastic Learning Automata (SLA) -- 3 Results and Discussion -- 3.1 Performance Measures. 505 8 3.2 Performance Comparison of Existing and Proposed Methods for DIP and SCOP Datasets -- 4 Conclusion -- References -- Economic Load Dispatch Problem with Valve-Point Loading Effect Using DNLP Optimization Using GAMS -- 1 Introduction -- 2 Economic Load Dispatch Mathematical Model -- 2.1 Constraints -- 2.2 Procedure -- 2.3 Contributions of Proposed Method -- 3 Results -- 4 Conclusions -- References -- Solar Radio Spectrum Classification Based on ConvLSTM -- 1 Introduction -- 2 Solar Radio Spectrum Dataset -- 2.1 The Introduction of SBRS Dataset -- 2.2 Dataset Extension -- 3 Pre-processing of Solar Radio Spectrums -- 3.1 Channel Normalization -- 3.2 Down-Sampling -- 4 Solar Radio Spectrum Classification Model Based on ConvLSTM -- 5 Experiment Results and Analysis -- 6 Conclusion -- References -- Particle Swarm Optimization-Based Neural Network for Wireless Heterogeneous Networks -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Work -- 4 Results -- 5 Conclusion -- References -- Impact Analysis of COVID-19 on Various Indian Sectors -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 4 Dataset -- 5 Screen time Analysis -- 5.1 Hypothesis Testing -- 6 Industrial Analysis -- 6.1 Information Technology -- 6.2 Fast-moving Consumer Goods (FMCG) -- 6.3 Hospitality -- 6.4 Aviation -- 7 Conclusion -- References -- Emotion Recognition in Speech Using MFCC and Classifiers -- 1 Introduction -- 2 Lıterature Revıew -- 3 Methodology -- 3.1 Emotions -- 3.2 Data -- 3.3 Dataset -- 3.4 Feature Extraction -- 3.5 Mel-frequency Cepstral Coefficient -- 4 Results -- 5 Conclusion -- References -- A Comparative Analysis on Image Caption Generator Using Deep Learning Architecture-ResNet and VGG16 -- 1 Introduction -- 2 Related Works -- 3 Comparison of Image Generator Using ResNet-50 and VGG16 -- 3.1 Image Preprocessing -- 3.2 Image Feature Extraction. 505 8 4 Text Feature Understanding Using LSTM -- 5 Results and Discussion -- 6 Conclusion -- References -- Corona Warrior Smart Band -- 1 Introduction -- 2 Literature Survey -- 3 Block Diagram and Working Principle -- 4 Implementation Platform -- 5 Results -- 6 Conclusion -- References -- Cellular Learning Automata: Review and Future Trend -- 1 Introduction -- 2 Cellular Automata (CA) -- 3 Learning Automata (LA) and Reinforcement Learning (RL) -- 4 Cellular Learning Automata (CLA) -- 5 Wireless Sensor and Actuator Networks (WSAN) -- 6 Future Trends -- 7 Conclusion -- References -- Computer Vision and Machine Learning-Based Techniques for Detecting the Safety Violations of COVID-19 Scenarios: A Review -- 1 Introduction -- 2 Related Work -- 2.1 Survey on Face Mask Detection -- 2.2 Survey on Social Distancing Detection -- 2.3 Survey on People Count Detection -- 2.4 Comparison Table of Literature Review -- 3 Outcome of Literature Review -- 4 Datasets -- 5 Challenges and Future Perspectives -- 6 Conclusion -- References -- Stigmergy-Based Collision-Avoidance Algorithm for Self-Organising Swarms -- 1 Introduction -- 2 Multi-agent Collision Avoidance Based on Stigmergy -- 3 Numerical Experiments -- 4 Conclusions -- References -- Handling Security Issues in Software-defined Networks (SDNs) Using Machine Learning -- 1 Introduction -- 2 Need of SDN -- 3 SDN and NFV -- 4 Security Issues in SDN -- 4.1 Hardware Security Issues -- 4.2 Security Threats at Software Level -- 5 Early Approaches for Securing SDN -- 5.1 Intrusion Detection and Prevention System (IDPS) for SDN -- 5.2 Intrusion Tolerant System (ITS) for SDN -- 5.3 Stateful Firewall for SDN -- 5.4 Framework for DDOS Detection and Prevention -- 6 Securing SDN with Machine Learning -- 6.1 Supervised ML for SDN -- 6.2 Unsupervised ML Algorithm for SDN -- 6.3 Semi-supervised Learning Approaches for SDN. 505 8 6.4 Machine Learning-based NIDS for SDN -- 7 Issues in Existing ML-based SDN -- 8 Conclusion -- 9 Future Scope -- References -- Multi-purpose Web Application Honeypot to Detect Multiple Types of Attacks and Expose the Attacker's Identity -- 1 Introduction -- 2 Related Work -- 3 Methods Used -- 3.1 Honeypot -- 3.2 GUI -- 3.3 Controller -- 3.4 Models -- 3.5 Sequence of Events -- 4 Proposed System -- 4.1 System Working -- 4.2 Overcoming Brute Force Script Attack -- 4.3 Overcoming Static Resource Attack -- 4.4 Overcoming Web Scraping Script (WSS) Attack -- 4.5 Overcoming GET/POST Request -- 4.6 Advantages of the Proposed Method -- 5 Experimental Results -- 6 Conclusion and Future Scope -- References -- An Empirical Approach for Tuning an Autonomous Mobile Robot in Gazebo -- 1 Introduction -- 2 Related Works -- 3 Related Theory -- 3.1 Sensors -- 3.2 Light Detection and Ranging (LIDAR) -- 3.3 Inertial Measurement Unit (IMU) -- 3.4 Adaptive Monte Carlo Localization (AMCL) -- 3.5 Navigation -- 4 Methodology -- 4.1 Costmap Parameters -- 4.2 Planner Parameters -- 5 Experimentation Result -- 6 Result Analysis -- 7 Conclusion -- References -- An Investigation on Computational Intelligent Solutions for Highly Dynamic Wireless Sensor Networks -- 1 Introduction -- 2 Computational Intelligent Paradigms -- 2.1 Fuzzy Logic (FL) -- 2.2 Evolutionary Algorithms (EA) -- 2.3 Artificial Neural Networks (ANN) -- 2.4 Swarm Intelligence (SI) -- 3 WSN Challenges -- 4 Related Work -- 4.1 CI Approaches for Energy Management -- 4.2 Heuristic Solutions for Packet Routing -- 4.3 Traffic Management with Channel Dynamics Using CI Methods -- 5 Conclusion -- References -- A Study of Underwater Image Pre-processing and Techniques -- 1 Introduction -- 2 Literature Review -- 3 Types of Image Pre-processing -- 3.1 Color Conversion -- 4 Binarization -- 5 Filtering -- 6 Resizing. 505 8 7 Techniques of Underwater Image Processing. 588 Description based on print version record. 504 Includes bibliographical references and index. 650 0 Natural computation. 776 08 |iPrint version:Smys, S. |tComputational Vision and Bio-Inspired Computing |dSingapore : Springer Singapore Pte. Limited,c2022 |z9789811695728 700 1 Smys, S., |eeditor. 700 1 Tavares, João Manuel R. S., |eeditor. 700 1 Balas, Valentina Emilia, |eeditor. 830 0 Advances in Intelligent Systems and Computing 906 BOOK