LEADER 00998nam0-22003251i-450- 001 990004569590403321 005 20101115200230.0 035 $a000456959 035 $aFED01000456959 035 $a(Aleph)000456959FED01 035 $a000456959 100 $a19990604d1905----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $aa-------00--- 200 1 $aManuale di storia del Medio evo dal 476 al 1313 per le scuole medie superiori e per le persone colte$fArturo Galanti 210 $aTorino$cParavia$d1905 215 $a480 p.$cill.$d21 cm 225 1 $aBiblioteca di storia e geografia 610 0 $aMedioevo$aStoria 700 1$aGalanti,$bArturo$0176937 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990004569590403321 952 $a6-VIIIA3$bS.I.$fFLFBC 952 $a6/VIIIA71$bBIBL.2257$fFLFBC 952 $a6/VIII A 71$bBIBL.2257$fFLFBC 959 $aFLFBC 996 $aManuale di storia del Medio Evo dal 476 al 1313$9543238 997 $aUNINA LEADER 07311nam 22007215 450 001 9910698651603321 005 20251113193203.0 010 $a9789819916481 010 $a9819916488 024 7 $a10.1007/978-981-99-1648-1 035 $a(CKB)5710000000117069 035 $a(DE-He213)978-981-99-1648-1 035 $a(MiAaPQ)EBC7238828 035 $a(Au-PeEL)EBL7238828 035 $a(PPN)269656324 035 $a(MiAaPQ)EBC7237217 035 $a(EXLCZ)995710000000117069 100 $a20230414d2023 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNeural Information Processing $e29th International Conference, ICONIP 2022, Virtual Event, November 22?26, 2022, Proceedings, Part VII /$fedited by Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2023. 215 $a1 online resource (XXXV, 569 p. 193 illus., 169 illus. in color.) 225 1 $aCommunications in Computer and Information Science,$x1865-0937 ;$v1794 311 08$a9789819916474 311 08$a981991647X 320 $aIncludes bibliographical references and index. 327 $aApplications 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. 330 $aThe four-volume set CCIS 1791, 1792, 1793 and 1794 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22?26, 2022. The 213 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements. 410 0$aCommunications in Computer and Information Science,$x1865-0937 ;$v1794 606 $aPattern recognition systems 606 $aArtificial intelligence 606 $aComputer vision 606 $aComputer networks 606 $aEducation$xData processing 606 $aAutomated Pattern Recognition 606 $aArtificial Intelligence 606 $aComputer Vision 606 $aComputer Communication Networks 606 $aComputers and Education 615 0$aPattern recognition systems. 615 0$aArtificial intelligence. 615 0$aComputer vision. 615 0$aComputer networks. 615 0$aEducation$xData processing. 615 14$aAutomated Pattern Recognition. 615 24$aArtificial Intelligence. 615 24$aComputer Vision. 615 24$aComputer Communication Networks. 615 24$aComputers and Education. 676 $a745.05 702 $aTanveer$b Mohammad 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910698651603321 996 $aNeural Information Processing$92554499 997 $aUNINA