Artificial Neural Networks and Machine Learning – ICANN 2024

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

AvMichael Wand,Kristína Malinovská

Häftad, Engelska, 2024

Del 15021 i serien Lecture Notes in Computer Science

834 kr

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Beskrivning

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

Utgivningsdatum:2024-09-17
Mått:155 x 235 x 20 mm
Vikt:552 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:330
Förlag:Springer International Publishing AG
ISBN:9783031723469

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Tillämpad datateknik inom Data och IT

Innehållsförteckning

.- 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.