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Titlebook: Advanced Intelligent Computing Technology and Applications; 20th International C De-Shuang Huang,Wei Chen,Yijie Pan Conference proceedings

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樓主: fundoplication
51#
發(fā)表于 2025-3-30 12:16:05 | 只看該作者
Fusion of Saliency and Edge Map for Multi-operator Image Retargeting Algorithmnd structural details of the original image while removing the minimum energy seams, thus avoiding image artifacts and distortions. To prevent excessive seam carving from distorting the image, we protect the main structure of the image by combining the seam carving and scaling algorithms and adaptiv
52#
發(fā)表于 2025-3-30 15:04:38 | 只看該作者
Color Image Steganography Based on Two-Channel Preprocessing and U-Net Networkto recover the secret image. The experimental outcomes indicate that the proposed model increases the visual effect of images, with cover images PSNR and SSIM reaching 40.36 dB and 98.18%, respectively. Therefore, the model can effectively hide images during information transmission and prevent atta
53#
發(fā)表于 2025-3-30 19:46:05 | 只看該作者
Application of a Hybrid Particle Image Velocimetry Method Based on Window Function in the Field of Teffectiveness of the method proposed in this paper. The results confirm that the method proposed in this article has a significant effect on turbulent particle images, and is always more accurate in generating the initial velocity field of turbulence than based on cross-correlation algorithms. It ca
54#
發(fā)表于 2025-3-30 20:59:31 | 只看該作者
55#
發(fā)表于 2025-3-31 01:26:49 | 只看該作者
A Two-Stage Coupled Learning Network for Image Deblurringn the first stage, we introduce a novel two-decoder architecture with collaborative learning to preliminarily decouple blur features and mitigate the learning complexity of the network. In the second stage, we propose a coupled learning module (CLM) and a feature enhancement block (FEB) to constrain
56#
發(fā)表于 2025-3-31 06:49:37 | 只看該作者
57#
發(fā)表于 2025-3-31 11:44:45 | 只看該作者
58#
發(fā)表于 2025-3-31 17:14:40 | 只看該作者
Image Captioning with Masked Diffusion Modelive experiments and ablation studies on the MSCOCO benchmark. The experimental results demonstrate that our masked diffusion model combined with the CLIP model achieves highly competitive performance in caption generation tasks. Not only does it significantly improve generation speed, but it also yi
59#
發(fā)表于 2025-3-31 19:55:39 | 只看該作者
60#
發(fā)表于 2025-3-31 22:49:54 | 只看該作者
https://doi.org/10.1007/978-981-97-5603-2Evolutionary Computing and Learning; Swarm Intelligence and Optimization; Neural Networks; Signal Proce
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