凝乳 发表于 2025-3-30 11:29:38
Image Super-Resolution via Deep Dictionary Learningthe deep features of the image, but also the trained dictionary may be relatively large. This paper proposes a new deep dictionary learning model. First, after preprocessing the images of the training set, the dictionary is trained by the deep dictionary learning method, and the super-resolution recIntegrate 发表于 2025-3-30 14:50:45
http://reply.papertrans.cn/47/4615/461482/461482_52.pngostrish 发表于 2025-3-30 17:05:52
http://reply.papertrans.cn/47/4615/461482/461482_53.png外向者 发表于 2025-3-30 21:30:08
http://reply.papertrans.cn/47/4615/461482/461482_54.png杀死 发表于 2025-3-31 02:51:00
http://reply.papertrans.cn/47/4615/461482/461482_55.png释放 发表于 2025-3-31 05:27:41
Research on Strategies for Tripeaks Variant with Various Layoutseaks variant games and assist in level design, this paper investigates the playing strategies for Tripeaks variant games. Firstly, three heuristic strategies based on player experience are proposed. Then, reinforcement learning agents are trained and tested on different datasets to evaluate their ge反应 发表于 2025-3-31 09:29:37
http://reply.papertrans.cn/47/4615/461482/461482_57.pngresilience 发表于 2025-3-31 13:26:27
ACMA-GAN: Adaptive Cross-Modal Attention for Text-to-Image Generationd. Recently, multi-stage conditional generative adversarial networks based on word attention are the mainstream of Text-to-Image generation. A close examination of these methods reveals two fundamental issues. Firstly, the granularity difference between the words and local image features makes the w疲劳 发表于 2025-3-31 19:04:06
http://reply.papertrans.cn/47/4615/461482/461482_59.png喃喃而言 发表于 2025-4-1 00:39:39
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