Fourth International Conference on Image Processing and Capsule Networks : Icipcn 2023

• Record Nr.: UNINA9910765485303321
• Autore: Shakya Subarna
• Pubbl/distr/stampa: Singapore : , : Springer, , 2024; ©2023
• ISBN: 9789819970933; 9819970938
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (741 pages)
• Collana: Lecture Notes in Networks and Systems Series ; ; v.798
• Altri autori (Persone): TavaresJoão Manuel R. S; Fernández-CaballeroAntonio; PapakostasGeorge
• Soggetti: Image processing; Neural networks (Computer science)
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Intro -- Preface -- Contents -- Editors and Contributors -- Modern Challenges and Limitations in Medical Science Using Capsule Networks: A Comprehensive Review -- 1 Introduction -- 2 What Are the Modern Challenges in Medical Science? -- 3 How Medical Science Problems Can Be Solved Using Capsule Networks? -- 4 How to Analyze a Large Amount of Data in Drug Development Using Capsule Networks? -- 5 Research Questions -- 6 Related Work -- 7 Existing Work Limitations -- 8 Methodology -- 8.1 CapsNet -- 8.2 ConvCaps -- 9 Research Motivation -- 10 Problem Statement -- 11 Discussion -- 12 Existing Research Limitations -- 13 Identified Research Gaps -- 14 Limitations of the Capsule Networks for Medical Science Research -- 15 Current Applications -- 15.1 Micro-Robot Adaptation -- 15.2 Network Biology -- 16 Open Challenges and Future Redirections -- 16.1 Transfer Learning -- 17 Conclusion and Future Work -- References -- Studies on Movie Soundtracks Over the Last Five Years -- 1 Introduction -- 2 Methodology -- 3 Results -- 3.1 Soundtrack Influence on the Audiovisual Narrative of Movies -- 3.2 The Creative Process of a Movie Soundtrack -- 3.3 Music and Political Communication -- 3.4 ; Soundtrack as a Study Instrument -- 4 Discussion and Conclusions -- References -- Blind Source Separation of EEG Signals Using Wavelet and EMD Decomposition -- 1 Introduction -- 2 Material and Methods -- 2.1 Datasets -- 2.2 Empirical Mode Decomposition -- 2.3 Wavelet Transform -- 2.4 Blind Source Separation -- 2.5 Proposed Method -- 3 Results -- 4 Conclusion -- References -- Image Extraction Approaches for Density Count Measurement in Obstruction Renography Using Radiotracer 99mTc-DTPA -- 1 Introduction -- 1.1 Characteristics of DTPA in Renal Imaging -- 2 Materials and Methods -- 3 Results -- 3.1 Mean and Standard Deviation of Transforms -- 3.2 Radioactive Counts Measurement.; 3.3 Statistical Correlation Findings -- 4 Discussion -- 4.1 Statistical Analysis for Clinical Validation -- 5 Conclusion -- References -- Deep Short-Term Long Memory Technique for Respiratory Lung Disease Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Problem of Statement -- 3 Proposed Methodology -- 3.1 Dataset Collection -- 3.2 Image Pre-processing -- 3.3 Local Binary Gabor Filter -- 3.4 Deep Short-Term Long Memory (DSTLM) -- 4 Analyses and Discussions of Experimental Results -- 4.1 Evaluation Matrix -- 5 Conclusion -- References -- Utilizing Satellite Imagery for Flood Monitoring in Urban Regions -- 1 Introduction -- 2 Related Work -- 3 Major Techniques Used -- 3.1 Ordered Weighted Averaging -- 3.2 Spectral Indices -- 3.3 Region Growing -- 3.4 Double Scattering -- 3.5 Bootstrap Method -- 3.6 Fuzzy Logic-Based Post Classification -- 3.7 Probabilistic Flood Mapping -- 3.8 Normalized Difference Vegetation Index -- 3.9 Modified Normalized Difference Water Index -- 3.10 Normalized Difference Water Index (NDWI) -- 3.11 CNN (Convolutional Neural Network) -- 4 Literature Survey -- 5 Observation on Literature Survey -- 6 Proposed Architecture -- 7 Methodology -- 7.1 Training -- 7.2 Testing -- 8 Conclusion and Future Scope -- References -- Optimizing Permutations in Biclustering Algorithms -- 1 Introduction -- 1.1 Literature Survey -- 1.2 Aim of the Study -- 2 Materials and Methods -- 2.1 Datasets -- 2.2 Device Specifications and Software -- 2.3 Structural Magnetic Resonance Imaging Data -- 2.4 Modified N-BiC Algorithm -- 2.5 Evaluation Measures -- 3 Results and Discussion -- 3.1 Simulated Dataset -- 3.2 PPMI Dataset -- 3.3 Performance of Modified N-BiC on PPMI Dataset -- 4 Research Limitations/Implications -- 5 Originality and Value -- 6 Conclusion and Future Research Work -- References.; Extracting Graphs from Plant Leaf Venations Using Image Processing -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Image Acquisition -- 3.2 Preprocessing -- 3.3 Ground Truth (GT) Tracing -- 3.4 Vein Extraction and Graph Conversion -- 4 Results -- 4.1 Performance Analysis -- 4.2 Graph Metrics Results -- 5 Conclusion and Recommendation -- References -- Multispectral Fusion of Multisensor Image Data Using PCNN for Performance Evaluation in Sensor Networks -- 1 Introduction -- 2 Related Work -- 3 Research Methodology -- 3.1 Image Preprocessing -- 3.2 Image Enhancement -- 3.3 Image Fusion -- 3.4 Image Quality Enhancement -- 3.5 Image Reverse-Fusion Process -- 4 Results and Discussion -- 5 Conclusion -- References -- U-Net-Based Segmentation of Coronary Arteries in Invasive Coronary Angiography -- 1 Introduction -- 2 Related Work -- 2.1 Medical Imaging Works for Coronary Arteries -- 2.2 Image Segmentation with U-Net -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Method -- 4 Results and Discussion -- 5 Conclusion -- References -- Change Detection for Multispectral Remote Sensing Images Using Deep Learning -- 1 Introduction -- 1.1 Applications of Remote Sensing -- 2 Proposed Work -- 2.1 Datasets -- 2.2 Architecture -- 2.3 ; Proposed Work -- 3 Result Analysis -- 4 Conclusion -- References -- Explainable AI for Black Sigatoka Detection -- 1 Introduction -- 1.1 Backgroung and Motivation -- 1.2 Research Contribution -- 2 Research Problem Definition -- 3 Research Approach and Methodology -- 3.1 Data Collection and Preprocessing -- 3.2 Model Implementation -- 4 Major Research Findings -- 4.1 Model Evaluation -- 4.2 XAI Results -- 5 Practical Implications -- 6 Research Limitations -- 7 Originality/Value -- 8 Conclusion and Future Research Work -- 8.1 Conclusion -- 8.2 Future Works -- References.; Modified U-Net and CRF for Image Segmentation of Crop Images -- 1 Introduction -- 2 Related Work -- 2.1 U-Net -- 2.2 Residual Block (ResBlock) -- 2.3 Residual Path -- 3 Proposed Architecture -- 3.1 Selection of Algorithm -- 3.2 Conditional Random Field (CRF) -- 4 Results and Discussions -- 4.1 Qualitative Evaluation -- 4.2 Quantitative Evaluation -- 4.3 Retention of Spatial Information -- 5 Conclusion -- References -- Securing Data in the Cloud: The Application of Fuzzy Identity Biometric Encryption for Enhanced Privacy and Authentication -- 1 Introductıon -- 2 Related Work -- 3 System Model -- 4 Basic Fuzzy Selective-ID -- 5 Conclusion -- References -- Quantum Convolutional Neural Network for Agricultural Mechanization and Plant Disease Detection -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Feature Extraction -- 3.3 Segmentation -- 3.4 Classification -- 4 Results and Discussion -- 4.1 State of the Art -- 5 Conclusion -- References -- Innovative Method for Alzheimer's Disease Detection Using Convolutional Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Dataset Description -- 3.2 Dataset Preprocessing -- 3.3 Model Architecture and Design -- 4 Result Analysis and Discussion -- 4.1 Experimental Setup -- 4.2 Result Analysis and Performance Evaluation -- 5 Conclusion -- References -- Segmentation of White Matter Lesions in MRI Images Using Optimization-Based Deep Neural Network -- 1 Introduction -- 2 Related Work -- 2.1 Research Problem -- 3 Methodology -- 3.1 Harris hawk's Optimization (HHO) -- 3.2 Proposed HHO-DCNN for WML Segmentation -- 3.3 Architecture of CNN -- 4 Results and Discussion -- 4.1 Dataset -- 4.2 Quantitative Evaluation -- 5 Conclusion -- References -- A New Multi-level Hazy Image and Video Dataset for Benchmark of Dehazing Methods -- 1 Introduction.; 2 Related Work -- 2.1 Traditional Methods -- 2.2 Deep Learning-Based Methods -- 3 Datasets -- 4 IMF Dataset (IMFD) -- 5 Experiment -- 6 Results and Discussion -- 7 Conclusion -- References -- Creative AI Using DeepDream -- 1 Introduction -- 1.1 Convolution Neural Network -- 1.2 What is DeepDream? -- 1.3 Motivation -- 2 Literature Survey -- 3 Methodology -- 3.1 Tools Used -- 3.2 DeepDream Implementation Using Tensorflow -- 3.3 Proposed System -- 4 Result -- 5 Conclusion -- References -- Tuberculosis Bacteria Detection Using Deep Learning Techniques -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Dataset Description -- 3.2 Dataset Pre-processing -- 3.3 System Architecture and Implementation -- 4 Results and Discussion -- 4.1 Experimental Results -- 4.2 Performance Evaluation -- 5 Conclusion -- References -- An Enhanced Real-Time System for Wrong-Way and Over Speed Violation Detection Using Deep Learning -- 1 Introduction -- 2 Literature Survey -- 3 Project Methodology -- 3.1 YOLOv3 Algorithm -- 3.2 Working of YOLOv3 -- 3.3 YOLOv3 Network Architecture -- 3.4 Kalman Filter -- 3.5 Wrong-Way Traffic Violation Detection Algorithm -- 3.6 Over Speed Violation Detection Algorithm -- 4 Experimental Results -- 4.1 Vehicle Detection and Tracking -- 4.2 Wrong-Way Violation Detection -- 4.3 Over Speed Violation Detection -- 5 Conclusion -- References -- U-Net-Based ; Denoising Autoencoder Network for De-Speckling in Fetal Ultrasound Images -- 1 Introduction -- 2 Existing Methods -- 3 Proposed Method -- 3.1 U-Net-Based Denoising Network -- 3.2 U-shaped Dilated Convolution Denoising Autoencoder Network -- 3.3 U-Net-Based Denoising Autoencoder Network -- 4 Result and Discussion -- 4.1 Dataset -- 4.2 Adding Speckle Noise -- 4.3 Effect of Dropout -- 4.4 Effects of Accuracy and Loss -- 4.5 Effects on Different Noise Levels -- 5 Conclusion.; References.
• Sommario/riassunto: This book is a collection of proceedings from the Fourth International Conference on Image Processing and Capsule Networks (ICIPCN 2023). It offers a comprehensive overview of recent research and developments in image processing, capsule network algorithms, and models. The conference aims to bridge academia and industry, facilitating the exchange of significant research experiences and solutions to practical challenges in imaging science. With contributions from researchers worldwide, the book covers topics such as medical imaging, remote sensing, and artificial intelligence applications in image processing. It is a valuable resource for researchers, engineers, and professionals interested in the latest advancements in these fields.