Left-Atrium 发表于 2025-3-25 04:54:23
http://reply.papertrans.cn/83/8234/823394/823394_21.pngfledged 发表于 2025-3-25 09:24:47
http://reply.papertrans.cn/83/8234/823394/823394_22.png膝盖 发表于 2025-3-25 11:41:10
Gesture Recognition on Video Dataacross a sequence of frames..Current approaches to hand gesture recognition face limitations. Some methods rely solely on visual inputs, processing them without considering occlusion and illumination issues, leading to performance degradation. Others employ wearable sensors, which can be bulky and p幼儿 发表于 2025-3-25 17:44:38
http://reply.papertrans.cn/83/8234/823394/823394_24.png在前面 发表于 2025-3-25 20:05:09
Learning Facial Expression Recognition In-the-Wild from Synthetic Data Based on an Ensemble of Lightition. We study various ensemble approaches that combine the lightweight MT-EmotiEffNet, attention-based transformer, and the graph-based model. The models have been implemented on an edge device (Jetson Nano) to be integrated into a demo application for video analytics to evaluate their performance银版照相 发表于 2025-3-26 01:36:29
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http://reply.papertrans.cn/83/8234/823394/823394_27.png合适 发表于 2025-3-26 11:10:47
http://reply.papertrans.cn/83/8234/823394/823394_28.png做事过头 发表于 2025-3-26 16:00:41
http://reply.papertrans.cn/83/8234/823394/823394_29.pngemployor 发表于 2025-3-26 18:36:23
Prompt-Tuning for Targeted Sentiment Analysis in Russian-tuning BERT-like models were explored. The best result was achieved when incorporating external knowledge into the prompt verbalizer. We demonstrate that prompt-tuning methods help achieve high results while being less computationally intensive than other fine-tuning and ensembling strategies.