垫子
发表于 2025-3-26 22:43:10
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进入
发表于 2025-3-27 02:27:11
,Earth’s Nearest Neighbor: The Moon,You can actually tell that the Moon is our nearest neighbor. The changing appearance of the Moon is shown and discussed through photographs of the kind you can take yourself. It is shown why lunar craters, seas and oceans are roughly round. It is also shown how to record eclipses of the Sun and Moon.
nonchalance
发表于 2025-3-27 07:56:59
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爵士乐
发表于 2025-3-27 11:19:40
Observing the Solar System from Your Armchair,NASA puts much of its space exploration data on the Internet, copyright free. Some military stuff is doubtless kept under wraps, but that is also off topic. Since the folks at NASA have been very busy bees since the dawn of space exploration, there is an awful lot of NASA material available.
小木槌
发表于 2025-3-27 17:34:23
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minimal
发表于 2025-3-27 21:30:58
useful internal saliency information. MSFRC is designed to aggregate multi-source features and reduce parameter imbalance between saliency features and boundary features. Compared with previous methods, more layers are applied to generate boundary features, which sufficiently leverage the complement
resistant
发表于 2025-3-28 00:25:59
Jane Clarkduring the feature transfer and refine the object edges. Finally, these three modules are merged into a unified and end-to-end network to predict the fine-grained boundary-preserving salient objects. Experimental results on three prevailing benchmarks show that our MineNet outperforms other competit
整理
发表于 2025-3-28 03:54:58
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Foam-Cells
发表于 2025-3-28 06:40:14
Jane Clarke attention features extracted based on the dual network are spatially mapped using a multi-layer perceptron (MLP). Then, the interaction dot product of the corresponding channels is performed on the attention features and the mapping features to guide the classification. Finally, to achieve good pe
他很灵活
发表于 2025-3-28 14:21:01
Jane Clarklleviate this problem, the second approach, multi-agent hybrid soft actor-critic (MAHSAC) is proposed. It extends hybrid soft actor-critic (HSAC) to multi-agent settings which introduces the idea of maximum entropy to strengthen the exploration of action space. Our experiments are running on a multi