Artificial Neural Networks and Machine Learning – ICANN 2024

33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part VI

Häftad, Engelska, 2024

AvMichael Wand,Kristína Malinovská,Jürgen Schmidhuber,Igor V. Tetko,Kristina Malinovska,Jurgen Schmidhuber

1 079 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

and fairness in machine learning.Part II - computer vision: classification; and computer vision: 3D methods. Part III - computer vision: anomaly detection; and topics in computer vision. Part IV - brain-inspired computing;

Produktinformation

Utgivningsdatum2024-09-17
Mått155 x 235 x 20 mm
Vikt552 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor330
FörlagSpringer International Publishing AG
ISBN9783031723469

Tillhör följande kategorier

Tillämpad datateknik inom Data och it
Systemvetenskap och AI inom Data och it
Hårdvara inom Data och it
Informationsteknik: allmänt inom Data och it
Artificiell intelligens inom Data och it

.- Multimodality..- ARIF: An Adaptive Attention-Based Cross-Modal Representation Integration Framework..- BVRCC: Bootstrapping Video Retrieval via Cross-matching Correction..- CAW: Confidence-based Adaptive Weighted Model for Multi-modal Entity Linking..- Cross-Modal Attention Alignment Network with Auxiliary Text Description for zero-shot sketch-based image retrieva..- Exploring Interpretable Semantic Alignment for Multimodal Machine Translation..- Modal fusion-Enhanced two-stream hashing network for Cross modal Retrieval..- Text Visual Question Answering Based on Interactive Learning and Relationship Modeling..- Unifying Visual and Semantic Feature Spaces with Diffusion Models for Enhanced Cross-Modal Alignment..- Federated Learning..- Addressing the Privacy and Complexity of Urban Traffic Flow Prediction with Federated Learning and Spatiotemporal Graph Convolutional Networks..- An Accuracy-Shaping Mechanism for Competitive Distributed Learning..- Federated Adversarial Learning for Robust Autonomous Landing Runway Detection..- FedInc: One-shot Federated Tuning for Collaborative Incident Recognition..- Layer-wised Sparsification Based on Hypernetwork for Distributed NN Training..- Security Assessment of Hierarchical Federated Deep Learning..- Time Series Processing..- ESSformer: Transformers with ESS Attention for Long-Term Series Forecasting..- Fusion of image representations for time series classification with deep learning..- HierNBeats: Hierarchical Neural Basis Expansion Analysis for Hierarchical Time Series Forecasting..- Learning Seasonal-Trend Representations and Conditional Heteroskedasticity for Time SeriesAnalysis..- One Process Spatiotemporal Learning of Transformers via Vcls Token for Multivariate Time Series Forecasting..- STformer: Spatio-Temporal Transformer for Multivariate Time Series Anomaly Detection..- TF-CL:Time Series Forcasting Based on Time-Frequency Domain Contrastive Learning.