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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
31#
發(fā)表于 2025-3-26 21:53:28 | 只看該作者
32#
發(fā)表于 2025-3-27 01:57:23 | 只看該作者
33#
發(fā)表于 2025-3-27 09:11:25 | 只看該作者
34#
發(fā)表于 2025-3-27 11:21:36 | 只看該作者
A Multimodal Fake News Detection Model with Self-supervised Unimodal Label Generationo focus on samples with highly differentiated modal information, we design an adaptive weight adjustment strategy to guide the model’s learning of unimodal information. Extensive experiments on two datasets demonstrate the effectiveness of our AFUG.
35#
發(fā)表于 2025-3-27 15:55:49 | 只看該作者
36#
發(fā)表于 2025-3-27 18:43:13 | 只看該作者
SkinDiff: A Novel Data Synthesis Method Based on Latent Diffusion Model for Skin Lesion Segmentationesponding masks, and then the Outpainting Background technique fills in the normal skin around the lesions to obtain full images. Experimental results show that expanding the skin lesion dataset using the proposed method can significantly improve the performance of the segmentation model.
37#
發(fā)表于 2025-3-27 22:32:30 | 只看該作者
Conference proceedings 2024 refereed proceedings of the 20th International Conference on Intelligent Computing, ICIC 2024, held in Tianjin, China, during August 5-8, 2024...The total of 863 regular papers were carefully reviewed and selected from 2189 submissions...This year, the conference concentrated mainly on the theories
38#
發(fā)表于 2025-3-28 04:10:27 | 只看該作者
MOD-YOLO: Improved YOLOv5 Based on Multi-softmax and Omni-Dimensional Dynamic Convolution for Multi-D-YOLO), which combines the proposed multi-softmax classification loss function with omni-dimensional dynamic convolution (ODConv). MOD-YOLO is evaluated on codebrim dataset and achieves the highest performance compared to existing SOTA models such as YOLO series and transformer-based series.
39#
發(fā)表于 2025-3-28 09:41:45 | 只看該作者
40#
發(fā)表于 2025-3-28 13:53:50 | 只看該作者
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