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Neural Information Processing: 31st International Conference, ICONIP 2024, Auckland, New Zealand, December 26, 2024, Proceedings, Part XI [Mīkstie vāki]

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  • Formāts: Paperback / softback, 422 pages, height x width: 235x155 mm, 128 Illustrations, color; 1 Illustrations, black and white; XXXIII, 422 p. 129 illus., 128 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2292
  • Izdošanas datums: 19-Aug-2025
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819666872
  • ISBN-13: 9789819666874
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Neural Information Processing: 31st International Conference, ICONIP 2024, Auckland, New Zealand, December 26, 2024, Proceedings, Part XIPalielināt
  • Formāts: Paperback / softback, 422 pages, height x width: 235x155 mm, 128 Illustrations, color; 1 Illustrations, black and white; XXXIII, 422 p. 129 illus., 128 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2292
  • Izdošanas datums: 19-Aug-2025
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819666872
  • ISBN-13: 9789819666874
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9789819666874.html

The sixteen-volume set, CCIS 2282-2297, constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024.
The 472 regular papers presented in this proceedings set were carefully reviewed and selected from 1301 submissions. These papers primarily focus on the following areas: Theory and algorithms; Cognitive neurosciences; Human-centered computing; and Applications.

Anchor STARK: Query Design for Transformer-Based Target Tracking.-
DACG-Net: A Dual Attention and Classifier Guided Network for Low-Light Image
Enhancement.- Improved Aggregated Contextual Transformations Based on U-Net
for Image Inpainting.- Mitigating Vanishing Activations in Deep CapsNets
Using Channel Pruning.- A Novel Data Synthesis Method by Integration of
Diffusion Model and GAN for Object Detection Task.- MOSSE-YOLOv8: A Two-Stage
Approach for Small-Target Arc Detection in High-Speed Railways.-
SAM-FL:Enhanced Generalizable Medical Image Segmentation via Sharpness-Aware
Minimization and Focal Loss.- CP2PNet: A General End-to-End Framework for
Plant Organs Counting and Phenological Stage Prediction.- Hierarchical
Prompt-Enhanced Image Generation Using Hyperbolic Space.- Efficient
Conditional Diffusion Model for Accurate Pedestrian
Trajectory Prediction.- MonoViM: Enhancing Self-supervised Monocular Depth
Estimation via Mamba.- An End-to-End rPPG-Based Face Anti-Spoofing Network
with Deception Enhancement Module.- Region-Aware Instruction-Guided Image
Editing with Attention-Weighted Feature Fusion.- Multi-view Self-supervised
3D Human Pose and Shape Estimation on SMPL.- WT-based Feature Enhancement
Network for Camouflaged Object Detection.- Multi-Headed Graph-based Attention
aided U-Net Model for Nuclei Segmentation.- Research and Implementation of
Fine-Grained Bird Image Classification.- LSC-YOLO: Small Target Defects
Detection Model for Wind Turbine Blade based on YOLOv9.- SAU: A Dual-Branch
Network to Enhance Long-Tailed Recognition via Generative Models.- Leveraging
local similarity for token merging in Vision Transformers.- Semi-Supervised
Domain Adaptation for All Weather Point Cloud Semantic Segmentation.-
Federated Learning for Blind Image Super-Resolution.- Towards Better
Text-to-Image Generation Alignment via Attention Modulation.- CLOFAI: A
Dataset of Real And Fake Image Classification Tasks for Continual Learning.-
AMSA-UNet: An Asymmetric Multiple Scales U-net Based on Self-attention for
Deblurring.- MT-Net: A Dual-Encoder Multiscale Medical Segmentation Model.-
ENHANCING ADVERSARIAL ROBUSTNESS OF DIFFUSION DENOISED SMOOTHING VIA IMAGE
SUPER-RESOLUTION.- A simultaneous hierarchical count data clustering and
feature selection based on Multinomial Nested Dirichlet Mixture using
the Minorization-Maximization framework.