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Titlebook: PRICAI 2024: Trends in Artificial Intelligence; 21st Pacific Rim Int Rafik Hadfi,Patricia Anthony,Quan Bai Conference proceedings 2025 The

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樓主: malfeasance
21#
發(fā)表于 2025-3-25 05:27:50 | 只看該作者
RSANet: Relationship-Aware Symmetric Alignment Network for?Fine-Grained Video-Text Retrievalample enhanced ranking loss is proposed to optimize the RSANet, which promotes the model output with a larger inter-class variation and a smaller intra-class variation. Extensive experiments on three public datasets, namely MSR-VTT, VATEX, and PKU FG-XMedia, show the effectiveness of RSANet surpasses state-of-the-art methods.
22#
發(fā)表于 2025-3-25 10:49:55 | 只看該作者
Zero-Shot Referring Image Segmentation with?Hierarchical Prompts and?Frequency Domain Fusion visual and text feature separately in the frequency domain to fully utilize feature information. Our method has been extensively tested on the RefCOCO, RefCOCO+, and RefCOCOg datasets, demonstrating significant improvements over existing zero-shot referring image segmentation methods.
23#
發(fā)表于 2025-3-25 14:32:00 | 只看該作者
Multi-scale Traffic Camera Image Detection Network Based on?Improved YOLOv8These results surpass the performance of leading detection algorithms. In addition, the model takes only 12.5 milliseconds to complete an inference, which makes it highly deployable and valuable for real-world applications.
24#
發(fā)表于 2025-3-25 18:54:33 | 只看該作者
Baitong Cui,Shuai Li,Jiayi Gui,Konglin Zhu,Shengchu Wang
25#
發(fā)表于 2025-3-25 21:15:59 | 只看該作者
Chao Wang,Zhongyuan Wang,Ruimin Hu,Xiaochen Wang,Wen Zhou
26#
發(fā)表于 2025-3-26 03:38:19 | 只看該作者
Query-Efficient Stealing Attacks Against Image Encodersbustness and generalization. Linear evaluation results on image datasets of various settings show that the proposed method achieves comparable or even better performance compared to existing attacks with only 25% of the query cost.
27#
發(fā)表于 2025-3-26 04:41:54 | 只看該作者
28#
發(fā)表于 2025-3-26 08:46:19 | 只看該作者
29#
發(fā)表于 2025-3-26 12:55:02 | 只看該作者
Video-Audio Multimodal Fall Detection Method model using Le2i and UP-Fall datasets. Additionally, we compared our findings with other fall detection methods. The outstanding results of our multimodal model indicate its superior performance compared to single fall detection models.
30#
發(fā)表于 2025-3-26 16:55:06 | 只看該作者
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