Neural information processing : 29th International Conference, ICONIP 2022, virtual event, November 22-26, 2022, proceedings, part VII / / edited by Mohammad Tanveer [and four others]

• Pubblicazione: Singapore : , : Springer, , [2023]; ©2023
• Edizione: 1st ed. 2023.
• Descrizione fisica: 1 online resource (XXXV, 569 p. 193 illus., 169 illus. in color.)
• Disciplina: 745.05
• Soggetto topico: Neural computers; Neural networks (Computer science)
• Persona (resp. second.): TanveerMohammad
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Applications II -- An Interpretable Multi-target Regression Method for Hierarchical Load Forecasting -- Automating Patient-Level Lung Cancer Diagnosis in Different Data Regimes -- Multi-level 3DCNN with Min-Max Ranking Loss for Weakly-supervised Video Anomaly Detection -- Automatically Generating Storylines from Microblogging Platforms -- Improving Document Image Understanding with Reinforcement Finetuning -- MSK-Net: Multi-source Knowledge Base Enhanced Networks for Script Event Prediction -- Vision Transformer-based Federated Learning for COVID-19 Detection using Chest X-ray -- HYCEDIS: HYbrid Confidence Engine for Deep Document Intelligence System -- Multi-level Network Based on Text Attention and Pose-guided for Person Re-ID -- Sketch Image Style Transfer based on Sketch Density Controlling -- VAE-AD: Unsupervised Variational Autoencoder for Anomaly Detection in Hyperspectral Images -- DSE-Net: Deep Semantic Enhanced Network for Mobile Tongue Image Segmentation -- Efficient-Nets and their Fuzzy Ensemble: An Approach for Skin Cancer Classification -- A Framework for Software Defect Prediction Using Optimal Hyper-parameters of Deep Neural Network -- Improved Feature Fusion by Branched 1-D CNN for Speech Emotion Recognition -- A Multi-modal Graph Convolutional Network for Predicting Human Breast Cancer Prognosis -- Anomaly detection in surveillance videos using transformer based attention model -- Change Detection in Hyperspectral Images using Deep Feature Extraction and Active Learning -- TeethU2Net: A Deep Learning-Based Approach for Tooth Saliency Detection in Dental Panoramic Radiographs -- The EsnTorch Library: Efficient Implementation of Transformer-Based Echo State Networks -- Wine Characterisation with Spectral Information and Predictive Artificial Intelligence -- MRCE: A Multi-Representation Collaborative Enhancement Model for Aspect-Opinion Pair Extraction -- Diverse and High-Quality Data Augmentation Using GPT for Named Entity Recognition -- Transformer-based Original Content Recovery from Obfuscated PowerShell Scripts -- A Generic Enhancer for Backdoor Attacks on Deep Neural Networks -- Attention Based Twin Convolutional Neural Network with Inception Blocks for Plant Disease Detection using Wavelet Transform -- A Medical Image Steganography Scheme with High Embedding Capacity to Solve Falling-Off Boundary Problem using Pixel Value Difference Method -- Deep Ensemble Architecture: A Region Mapping for Chest Abnormalities -- Privacy-Preserving Federated Learning for Pneumonia Diagnosis -- Towards Automated Segmentation of Human Abdominal Aorta and Its Branches Using a Hybrid Feature Extraction Module with LSTM -- p-LSTM: An explainable LSTM architecture for Glucose Level Prediction -- A Wide Ensemble of Interpretable TSK Fuzzy Classifiers with Application to Smartphone Sensor-based Human Activity Recognition -- Prediction of the Facial Growth Direction: Regression Perspective -- A Methodology for the Prediction of Drug Target Interaction using CDK Descriptors -- PSSM2Vec: A Compact Alignment-Free Embedding Approach for Coronavirus Spike Sequence Classification -- An optimized hybrid solution for IoT based lifestyle disease classification using stress data -- A Deep Concatenated Convolutional Neural Network-based Method to Classify Autism -- Deep Learning-based Human Action Recognition Framework to Assess Children on the Risk of Autism or Developmental Delays -- Dynamic Convolutional Network for Generalizable Face Anti-Spoofing -- Challenges Of Facial Micro-expression Detection and Recognition : A Survey -- Biometric Iris Identifier Recognition With Privacy Preserving Phenomenon: A Federated Learning Approach -- Traffic Flow Forecasting using Attention Enabled Bi-LSTM and GRU Hybrid Model -- Commissioning Random Matrix Theory and Synthetic Minority Oversampling Technique for Power System Faults Detection and Classification -- Deep reinforcement learning with comprehensive reward for stock trading -- Deep Learning based automobile identification application -- Automatic Firearm Detection in Images and Videos Using YOLO-based Model.
• Sommario/riassunto: The four-volume set CCIS 1791, 1792, 1793 and 1794 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22–26, 2022. The 213 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
• Titolo autorizzato: Neural Information Processing
• ISBN: 981-9916-48-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910698651603321
• Lo trovi qui: Univ. Federico II
• Serie: Communications in Computer and Information Science, . 1865-0937 ; ; 1794