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Neural Information Processing: 29th International Conference, ICONIP 2022, Virtual Event, November 22–26, 2022, Proceedings, Part VII de Mohammad Tanveer

Neural Information Processing: 29th International Conference, ICONIP 2022, Virtual Event, November 22–26, 2022, Proceedings, Part VII: Communications in Computer and Information Science, cartea 1794

Editat de Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt
en Limba Engleză Paperback – 15 apr 2023
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.
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Specificații

ISBN-13: 9789819916474
ISBN-10: 981991647X
Pagini: 569
Ilustrații: XXXV, 569 p. 193 illus., 169 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.84 kg
Ediția:1st ed. 2023
Editura: Springer Nature Singapore
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Singapore, Singapore

Cuprins

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.