Neural Information Processing 29th International Conference, ICONIP 2022, Virtual Event, November 22–26, 2022, Proceedings, Part VII /
Neural Information Processing 29th International Conference, ICONIP 2022, Virtual Event, November 22–26, 2022, Proceedings, Part VII / [electronic resource] :
edited by Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt.
- 1st ed. 2023.
- XXXV, 569 p. 193 illus., 169 illus. in color. online resource.
- Communications in Computer and Information Science, 1794 1865-0937 ; .
- Communications in Computer and Information Science, 1794 .
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 andtheir 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.
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.
9789819916481
10.1007/978-981-99-1648-1 doi
Pattern recognition systems.
Artificial intelligence.
Computer vision.
Computer networks .
Education--Data processing.
Automated Pattern Recognition.
Artificial Intelligence.
Computer Vision.
Computer Communication Networks.
Computers and Education.
Q337.5 TK7882.P3
006.4
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 andtheir 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.
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.
9789819916481
10.1007/978-981-99-1648-1 doi
Pattern recognition systems.
Artificial intelligence.
Computer vision.
Computer networks .
Education--Data processing.
Automated Pattern Recognition.
Artificial Intelligence.
Computer Vision.
Computer Communication Networks.
Computers and Education.
Q337.5 TK7882.P3
006.4