Artificial Neural Networks and Machine Learning - ICANN 2023

Idioma: inglés

Editorial: Springer, Springer Sep 2023, 2023

3031442032 / 9783031442032

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This item is printed on demand - Print on Demand Titel. Neuware -A Comparative Study of Sentence Embedding Models for Assessing Semantic Variation.- A Deep Learning based Method for Generating Holographic Acoustic Fields from Phased Transducer Arrays.- A Depth-guided Attention Strategy for Crowd Counting.- A Noise Convolution Network for Tampering Detection.- Attention-based Feature Interaction Deep Factorization Machine for CTR Prediction.- Block-level Stiffness Analysis of Residual Networks.- CKNA: Kernel Hyperparameters Optimization Method for Group-wise CNNs.- Conditional Convolution Residual Network for Efficient Super-Resolution.- Cross Attention with Deep Local Features for Few-shot Image Classification.- Deep Video Compression Based on 3D Convolution Artifacts Removal and Attention Compression Module.- Deep-learning Based Three Channel Defocused Projection Profilometry.- Depthwise Convolution with Channel Mixer: Rethinking MLP in MetaFormer for Faster and More Accurate Vehicle Detection.- DLUIO: Detecting Useful Investor Opinions by Deep Learning.- Dynamic obstacle avoidance for unmanned aerial vehicle using dynamic vision sensor.- Empirical Study on the Effect of Residual Networks on the Expressiveness of Linear Regions.- Energy Complexity Model for Convolutional Neural Networks.- Enhancing the Interpretability of Deep Multi-Agent Reinforcement Learning via Neural Logic Reasoning.- Evidential Robust Deep Learning for Noisy Text2text Question Classification.- FBPFormer: Dynamic Convolutional Transformer for Global-Local-Contexual Facial Beauty Prediction.- Heavy-Tailed Regularization of Weight Matrices in Deep Neural Networks.- Interaction of Generalization and Out-of-Distribution Detection Capabilities in Deep Neural Networks.- Long-distance Pipeline Intrusion Warning Based on Environment Embedding From Distributed Optical Fiber Sensing.- LSA3D: Lightweight Separate Asynchronous 3D Convolutional Neural Network for Gait Recognition.- MADNet: EEG-based Depression Detection using a Deep Convolution Neural Network Framework with Multi-dimensional Attention.- Maintenance automation using deep learning methods a case study from the aerospace industry.- MCASleepNet: Multimodal channel attention-based deep neural network for automatic sleep staging.- Multi-label Image Deep Hashing with Hybrid Loss of Global Center and Local Alignment.- Multi-relation Representation Learning based Deep Network for Patent Classification.- One Hip Wonder: 1D-CNNs Reduce Sensor Requirements for Everyday Gait Analysis.- Patches Channel Attention For Human Sitting Posture Recognition.- RA-Net: A Deep Learning Approach based on Residual Structure and Attention Mechanism for Image Copy-move Forgery Detection.- Rethinking CNN Architectures in Transformer Detectors.- Robustness of Biologically-inspired filter-based ConvNet to Signal Perturbation.- Self-Supervised Graph Convolution for Video Moment Retrieval.- Siamese Network based on MLP and Multi-head Cross Attention for Visual Object Tracking.- Taper Residual Dense Network for Audio Super-Resolution.- VPNDroid: Malicious Android VPN detection using a CNN-RF method.- Who breaks early, looses: goal oriented training of deep neural networks based on port Hamiltonian dynamics.- BLR:A multi-modal sentiment analysis model.- Detecting Negative Sentiment on Sarcastic Tweets for Sentiment Analysis.- Local or Global: The Variation in the Encoding of Style Across Sentiment and Formality.- Prompt-oriented Fine-tuning Dual Bert for Aspect-Based Sentiment Analysis.- Towards Energy-Efficient Sentiment Classification with Spiking Neural Networks.- Using Masked Language Modeling to Enhance BERT-based Aspect-Based Sentiment Analysis for Affective Token Prediction.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 580 pp. Englisch.…

N° de ref. del artículo 9783031442032

Título
Artificial Neural Networks and Machine Learning - ICANN 2023
Autor
Lazaros Iliadis
Editorial
Springer, Springer Sep 2023
Año de publicación
2023
Estado
Neu
Encuadernación
Taschenbuch
Idioma
inglés
ISBN 10
3031442032
ISBN 13
9783031442032
Peso del artículo
867 gramos
Dimensiones
235x155x32 mm

buchversandmimpf2000

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