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Titolo: |
Data, engineering and applications : select proceedings of IDEA 2021 / / edited by Sanjeev Sharma, [and four others]
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Pubblicazione: | Singapore : , : Springer, , [2022] |
©2022 | |
Descrizione fisica: | 1 online resource (693 pages) |
Disciplina: | 170 |
Soggetto topico: | Big data |
Persona (resp. second.): | SharmaSanjeev |
Nota di bibliografia: | Includes bibliographical references. |
Nota di contenuto: | Intro -- Contents -- Distortion Controlled Secure Reversible Data Hiding in H.264 Videos -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Distortion Cost Calculation and IPCM Selection -- 3.2 Data Embedding in IPCM Block -- 4 Results -- 4.1 PSNR Comparison -- 4.2 MSE Comparison -- 4.3 Embedding Capacity Comparison -- 5 Conclusion -- References -- A Method for Improving Efficiency and Security of FANET Using Chaotic Black Hole Optimization-Based Routing (BHOR) Technique -- 1 Introduction -- 2 Proposed Chaotic Black Hole Optimization-Based Routing (Chaotic BHOR) Technique -- 2.1 Key Link Exploitation -- 2.2 Link Energy Cost -- 2.3 Absolute Link Involvement -- 2.4 Black Hole Optimization (BHO) Technique -- 2.5 Absolute Drone Involvement -- 2.6 Working and Operation of Chaotic BHOR Technique -- 3 Result and Analysis -- 3.1 Packet Delivery Ratio (PDR) -- 3.2 End-To-End Delay (EED) -- 3.3 Power Expenses -- 3.4 Throughput -- 4 Conclusion -- References -- Machine Learning Techniques for Intrusion Detection System: A Survey -- 1 Introduction -- 2 Intrusion Detection -- 3 Intrusion Detection System -- 3.1 Types of IDS -- 3.2 Limitations of Traditional IDS -- 3.3 Survey on Intrusion Detection Method -- 4 Machine Learning -- 5 Machine Learning Techniques -- 5.1 Supervised Learning -- 5.2 Unsupervised Learning -- 5.3 Reinforcement Learning -- 6 Types of Machine Learning Techniques -- 6.1 Supervised Machine Learning Techniques -- 6.2 Unsupervised Machine Learning Techniques -- 7 Literature Survey -- 8 Conclusion -- References -- Software Fault Detection by Using Rider Optimization Algorithm (ROA)-Based Deep Neural Network (DNN) -- 1 Introduction -- 2 Software Quality -- 3 Software Faults and Testing -- 4 Objectives -- 5 Related Work -- 6 Datasets -- 7 Features Learning and Classifiers -- 8 Proposed Method -- 8.1 Dataset. |
9 Rider Optimization-Based Features Selection for KNN -- 10 Fitness Function -- 11 Deep Neural Network-Based Fault Detection -- 12 Results and Discussion -- 13 Performance Evaluation -- 14 Comparative Study -- 15 Conclusion -- References -- An Approach for Predicting Admissions in Post-Graduate Programme by Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Support Vector Regression -- 3.2 Hyperplane -- 3.3 Kernel -- 3.4 Boundary Line -- 3.5 Support Vector -- 4 Proposed Method -- 4.1 Data Pre-processing -- 4.2 Data Partitioning -- 4.3 Fitting Model -- 4.4 Accuracy Evaluation -- 4.5 Importance of Variables -- 5 Implementation and Experimentation -- 5.1 User Interface (UI) Working -- 5.2 Server Working -- 5.3 User Interface of Web-Application -- 5.4 Working Manifestation -- 5.5 Critical Analysis -- 6 Conclusion -- References -- A Survey on Various Representation Learning of Hypergraph for Unsupervised Feature Selection -- 1 Introduction -- 2 Feature Selection -- 2.1 Feature Selection Classification -- 3 Representation Learning -- 3.1 Representation Learning Applications -- 3.2 Latent Representation Learning -- 3.3 Hypergraph Learning -- 4 Optimization Techniques -- 5 Literature Survey -- 6 Conclusion -- References -- Adoption of Blockchain Technology for Storage and Verification of Educational Documents -- 1 Introduction -- 2 Developing -- 2.1 Possibility of Using the Distributed Registry for the Document Storage -- 2.2 Blockchain Technology Offers the Following Five Benefits [8] -- 3 Conclusion -- References -- Obstacle Collision Prediction Model for Path Planning Using Obstacle Trajectory Clustering -- 1 Introduction -- 2 Related Work -- 3 Proposed System -- 4 Experimental Results -- 5 Conclusion -- References -- Human Saliency Based Object Detection from Natural Images -- 1 Introduction. | |
2 Background of Saliency Detection Models -- 2.1 Context-Aware Saliency Detection Model -- 2.2 Graph-Based Visual Saliency -- 2.3 Spectral Residual Approach -- 2.4 Itti and Koch Model -- 3 Methodology -- 4 Experimental Results and Discussion -- 4.1 Dataset -- 4.2 System Specification -- 4.3 Discussion -- 5 Conclusion -- References -- Dynamic Education Background: Procure the Maximum Initiation from PBL for Education Naïve Bayes Algorithm for Machine Learning -- 1 Introduction -- 2 Knowledge Policy in Engineering Teaching: The Problem-Based Learning Approach (PBL) -- 3 Case Study: Issues and Context PBL -- 4 Naïve Bayes Machine Learning Platform Analysis and Discussion (PBL) -- 5 Conclusion -- References -- Hybrid Microarray Gene Data Classification Based on GA-ACO Optimization -- 1 Introduction -- 2 Literature Review -- 3 System Design -- 3.1 Genetic Algorithm -- 3.2 Ant Colony Optimization -- 3.3 Hybrid Algorithm -- 4 Result and Discussion -- 5 Conclusion -- References -- An In-Field Real-Time Automatic Weed Detection Using Deep Learning Techniques -- 1 Introduction -- 2 Related Work -- 3 Methodology and Approach -- 3.1 Methodology -- 3.2 Dataset Collection -- 3.3 Approach -- 4 Results and Discussion -- 4.1 Training -- 4.2 Performance Metrics -- 4.3 Result -- 5 Conclusion and Future Work -- References -- Sentiment Analysis of Indians Due to Conflict Between India and China at the Actual Line of Control in Galwan Valley, Ladakh -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Extracting Data -- 3.2 Data Cleaning -- 3.3 Natural Language Processing (NLP) -- 3.4 Getting Subjectivity and Polarity of Each Tweet -- 3.5 Assigning Positive, Negative, and Neutral Sentiments -- 4 Experimental Results -- 5 Conclusion -- References -- Feature Selection Using Information Gain for Software Effort Prediction Using Neural Network Model. | |
1 Introduction -- 2 Related Work -- 2.1 ANN for Software Effort Estimation -- 2.2 Feature Selection -- 2.3 Proposed Problem -- 3 Artificial Neural Network (ANN) -- 3.1 FITNET: Feed-Forward Neural Network with Multiple Layers -- 4 Experiment Design -- 4.1 Datasets -- 4.2 Overall Procedure -- 4.3 Evaluation Metrics -- 5 Results and Discussion -- 6 Conclusions and Future Possibilities -- References -- A Comprehensive Survey of Web and Mobile Apps for Fishermen -- 1 Introduction -- 1.1 Motivation -- 2 Literature Survey -- 2.1 Survey of Web Apps -- 2.2 Survey of Mobile Applications -- 3 Discussion on the Identified Web and Mobile Apps -- 3.1 Requirements of the Fishermen -- 4 Conclusion -- References -- Study of Machine Learning Classifiers for Intrusion Detection System -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Machine Learning Classifiers -- 4 Results and Discussion -- 5 Conclusion -- References -- The Analysis of Time Series Data -- 1 Introduction -- 2 Literature Review -- 2.1 Biopharmaceutical Community -- 2.2 Statistical Computing and Programming Environment -- 2.3 Roadmap -- 2.4 Popularity of the Internet -- 2.5 Spatial Associations and Trends in Mobility -- 2.6 Proxy for Inventive Product -- 2.7 Understanding of Technology -- 3 Methodology -- 4 Result and Observations -- 5 Conclusion and Future Scope -- References -- Computed Tomography Image Processing Methods for Lung Nodule Detection and Classification: A Review -- 1 Introduction -- 2 Existing Techniques -- 3 Result and Discussion -- 4 Conclusion -- References -- Implementation and Analyzing SURF Feature Detection and Extraction on WANG Images Using Custom Bag of Features Model -- 1 Introduction -- 2 Detection and Extraction of Local Features -- 2.1 Feature Detection and Extraction Using SURF -- 3 Bag of Visual Words -- 4 Classifier: SVM (Supervised Vector Machine). | |
5 Dataset, Implementation, and Results -- 5.1 Dataset -- 5.2 BOVW Bag of Feature Model -- 5.3 Algorithm BOVW for Bag of Feature Model -- 5.4 Implementation -- 5.5 Results -- 5.6 Analysis -- 6 Conclusions and Future Work -- References -- Machine Learning Approaches for Image-Based Screening of Cervical Cancer -- 1 Introduction -- 2 Approaches Used for Image-Based Applications -- 2.1 Traditional Machine Learning-Based Methods -- 2.2 Challenges with the Traditional Approaches -- 2.3 Deep-Learning-Based Methods -- 3 Dataset -- 3.1 Herlev Dataset -- 3.2 SIPaKMed Database -- 3.3 CRIC Searchable Image Database -- 3.4 Overlapping Cells Dataset of ISBI 2014 and ISBI 2015 Challenge -- 3.5 National Cancer Institute (NCI) -- 4 Performance Measures -- 4.1 Evaluation Metrics for Recognition Tasks at the Cellular-Level and Cervigram Images -- 4.2 Evaluation Metrics for Segmentation Task in ISBI 2014 and ISBI 2015 Challenge -- 5 Discussion and Conclusion -- References -- A Comparative Analysis of Image Steganography Based on Discrete Wavelet Transform (DWT) and Exploiting Modification Direction (EMD) -- 1 Introduction -- 2 Review -- 2.1 Least Significant Bit (LSB)-Based Methods -- 2.2 Least Significant Bit (LSB)-Based Methods -- 3 Discussion -- 4 Conclusion -- References -- Web Attack Detection Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Proposed System -- 4 System Implementation and Result Analysis -- 5 Conclusion -- References -- Pragmatic Analysis of Web Service Discovery Models and Architectures from a Qualitative Perspective -- 1 Introduction -- 2 Literature Review -- 3 Quantitative Analysis -- 4 Conclusion and Future Scope -- References -- An Integrated Semi-Supervised Learning Framework for Image Compression Using DCT, Huffman Encoding, and LZW Coding -- 1 Introduction -- 2 Literature Review -- 3 Methodology. | |
3.1 Compression Techniques. | |
Titolo autorizzato: | Data, Engineering and Applications ![]() |
ISBN: | 981-19-4687-6 |
Formato: | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 996495563703316 |
Lo trovi qui: | Univ. di Salerno |
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