Artificial Neural Networks and Machine Learning – ICANN 2024 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part II /
The ten-volume set LNCS 15016-15025 constitutes the refereed proceedings of the 33rd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2024, held in Lugano, Switzerland, during September 17–20, 2024. The 294 full papers and 16 short papers included in these proceedin...
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| Outros Autores: | , , , |
| Formato: | Recurso Electrónico livro electrónico |
| Idioma: | inglês |
| Publicado em: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
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| Edição: | 1st ed. 2024. |
| Colecção: | Lecture Notes in Computer Science,
15017 |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.1007/978-3-031-72335-3 |
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Sumário:
- -- Computer Vision: Classification.
- A WEAKLY SUPERVISED PART DETECTION METHOD FOR ROBUST FINE-GRAINED CLASSIFICATION.
- An Energy Sampling Replay-Based Continual Learning Framework.
- Coarse-to-Fine Granularity in MultiScale FeatureFusion Network for SAR Ship Classification. .-Multi-scale convolutional attention fuzzy broad network for few-shot hyperspectral image classification.
- Self Adaptive Threshold Pseudo-labeling and Unreliable Sample Contrastive Loss for Semi-supervised Image Classification.
- Computer Vision: Object Detection.
- CIA-Net:Cross-modal Interaction and Depth Quality-Aware Network for RGB-D Salient Object Detection.
- CPH DETR: Comprehensive Regression Loss for End-to-End Object Detection.
- DecoratingFusion: A LiDAR-Camera Fusion Network with the Combination of Point-level and Feature-level Fusion.
- EMDFNet: Efficient Multi-scale and Diverse Feature Network for Traffic Sign Detection.
- Global-Guided Weighted Enhancement for Salient Object Detection.
- KDNet: Leveraging Vision-Language Knowledge Distillation for Few-Shot Object Detection.
- MUFASA: Multi-View Fusion and Adaptation Network with Spatial Awareness for Radar Object Detection.
- One-Shot Object Detection with 4D-Correlation and 4D-Attention.
- Small Object Detection Based on Bidirectional Feature Fusion and Multi-scale Distillation. .-SRA-YOLO: Spatial Resolution Adaptive YOLO for Semi-Supervised Cross-Domain Aerial Object Detection.
- Computer Vision: Security and Adversarial Attacks.
- BiFAT: Bilateral Filtering and Attention Mechanisms in a Two-Stream Model for Deepfake Detection.
- EL-FDL: Improving Image Forgery Detection and Localization via Ensemble Learning.
- Generalizable Deepfake Detection with Unbiased Feature Extraction and Low-level Forgery Enhancement.
- Generative Universal Nullifying Perturbation for Countering Deepfakes through Combined Unsupervised Feature Aggregation.
- Noise-NeRF: Hide Information in Neural Radiance Field using Trainable Noise.
- Unconventional Face Adversarial Attack. Computer Vision: Image EnhancementComputer Vision: Image Enhancement.
- Computer Vision: Image Enhancement.
- A Study in Dataset Pruning for Image Super-Resolution.
- EDAFormer:Enhancing Low-Light Images with a Dual-Attention Transformer.
- Image Matting Based on Deep Equilibrium Models.
- Computer Vision: 3D Methods.
- ControlNeRF: Text-Driven 3D Scene Stylization via Diffusion Model.
- Interactive Color Manipulation in NeRF: A Point Cloud and Palette-driven Approach.
- Multimodal Monocular Dense Depth Estimation with Event-Frame Fusion using Transformer.
- SAM-NeRF: NeRF-based 3D Instance Segmentation with Segment Anything Model.
- Towards High-Accuracy Point Cloud Registration with Channel Self-Attention and Angle Invariance.