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Lieferstatus:	i.d.R. innert 5-10 Tagen versandfertig
Veröffentlichung:	November 2022
Genre:	EDV / Informatik
	Applications / computerscience / ConferenceProceedings / Informatics / Research
ISBN:	9783031200526
EAN-Code:	9783031200526
Verlag:	Springer
Einband:	Kartoniert
Sprache:	English
Dimensionen:	H 235 mm / B 155 mm / D 43 mm
Gewicht:	1194 gr
Seiten:	804
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

Improving Vision Transformers by Revisiting High-Frequency Components.- Recurrent Bilinear Optimization for Binary Neural Networks.- Neural Architecture Search for Spiking Neural Networks.- Where to Focus: Investigating Hierarchical Attention Relationship for Fine-Grained Visual Classification.- DaViT: Dual Attention Vision Transformers.- Optimal Transport for Label-Efficient Visible-Infrared Person Re-identification.- Locality Guidance for Improving Vision Transformers on Tiny Datasets.- Neighborhood Collective Estimation for Noisy Label Identification and Correction.- Few-Shot Class-Incremental Learning via Entropy-Regularized Data-Free Replay.- Anti-Retroactive Interference for Lifelong Learning.- Towards Calibrated Hyper-Sphere Representation via Distribution Overlap Coefficient for Long-Tailed Learning.- Dynamic Metric Learning with Cross-Level Concept Distillation.- MENet: A Memory-Based Network with Dual-Branch for Efficient Event Stream Processing.- Out-of-Distribution Detection with Boundary Aware Learning.- Learning Hierarchy Aware Features for Reducing Mistake Severity.- Learning to Detect Every Thing in an Open World.- KVT: k-NN Attention for Boosting Vision Transformers.- Registration Based Few-Shot Anomaly Detection.- Improving Robustness by Enhancing Weak Subnets.- Learning Invariant Visual Representations for Compositional Zero-Shot Learning.- Improving Covariance Conditioning of the SVD Meta-Layer by Orthogonality.- Out-of-Distribution Detection with Semantic Mismatch under Masking.- Data-Free Neural Architecture Search via Recursive Label Calibration.- Learning from Multiple Annotator Noisy Labels via Sample-Wise Label Fusion.- Acknowledging the Unknown for Multi-Label Learning with Single Positive Labels.- AutoMix: Unveiling the Power of Mixup for Stronger Classifiers.- MaxViT: Multi-axis Vision Transformer.- ScalableViT: Rethinking the Context-Oriented Generalization of Vision Transformer.- Three Things Everyone Should Know about Vision Transformers.- DeiT III: Revenge of the ViT.- MixSKD: Self-Knowledge Distillation from Mixup for Image Recognition.- Self-Feature Distillation with Uncertainty Modeling for Degraded Image Recognition.- Novel Class Discovery without Forgetting.- SAFA: Sample-Adaptive Feature Augmentation for Long-Tailed Image Classification.- Negative Samples Are at Large: Leveraging Hard-Distance Elastic Loss for Re-identification.- Discrete-Constrained Regression for Local Counting Models.- Breadcrumbs: Adversarial Class-Balanced Sampling for Long-Tailed Recognition.- Chairs Can Be Stood On: Overcoming Object Bias in Human-Object Interaction Detection.- A Fast Knowledge Distillation Framework for Visual Recognition.- DICE: Leveraging Sparsification for Out-of-Distribution Detection.- Invariant Feature Learning forGeneralized Long-Tailed Classification.- Sliced Recursive Transformer.