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Titlebook: Intelligence Science IV; 5th IFIP TC 12 Inter Zhongzhi Shi,Yaochu Jin,Xiangrong Zhang Conference proceedings 2022 IFIP International Federa

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21#
發(fā)表于 2025-3-25 06:00:03 | 只看該作者
DNM-SNN: Spiking Neural Network Based on Dual Network Modeles two key methods. Firstly, a dual model training method in training stage is proposed, which requires an additional auxiliary network same as the network used. Single model training is easy to fall into local optimal problems. By maintaining two networks, the same problem can be viewed from differ
22#
發(fā)表于 2025-3-25 10:17:28 | 只看該作者
A Deception Jamming Discrimination Method Based on Semi-supervised Learning with Generative Adversarsed method can achieve the same performance using less than 10% of the labelled data of existing algorithms. It reduces data requirements and enhances operational capabilities, which is better suited to real-world battlefield environments.
23#
發(fā)表于 2025-3-25 13:50:53 | 只看該作者
Fast Node Selection of?Networked Radar Based on?Transfer Reinforcement Learning nodes, transfer reinforcement learning is presented to fully leverage the previous knowledge. Experimental results show that our proposed method can quickly select the optimal and minimum radar nodes in a brief period, significantly improving the speed of radar node selection in the networked radar
24#
發(fā)表于 2025-3-25 18:12:08 | 只看該作者
Weakly Supervised Liver Tumor Segmentation Based on?Anchor Box and?Adversarial Complementary Learnin. Aiming at the problem that the current region mining method based on classification network is inaccurate and incomplete in object location, we use the Adversarial Complementary Learning module to make the network pay attention to more complete objects. We conduct analysis to validate the proposed
25#
發(fā)表于 2025-3-26 00:02:11 | 只看該作者
26#
發(fā)表于 2025-3-26 02:06:18 | 只看該作者
27#
發(fā)表于 2025-3-26 07:36:48 | 只看該作者
A Directed Search Many Objective Optimization Algorithm Embodied with?Kernel Clustering Strategy. Then, it improves them by the directed search method. DSMOA-KCS is compared with several existing state-of-the-art algorithms (NSGA-III, RSEA, and MOEADPas) on many-objective problems with 5 to 30 objective functions using the Inverted Generational Distance (IGD) performance metric. DSMOA-KCS eval
28#
發(fā)表于 2025-3-26 09:18:32 | 只看該作者
also um Festigkeitsrechnungen handelt, so braucht hier weder berücksichtigt zu werden, da? sich die Gr??e des Normaldruckes .. w?hrend des Eingriffs geringfügig ?ndert (Abschnitt 3) noch braucht die ebenfalls kleine Reibungskraft .. (Abschnitt 4) in Rechnung gestellt zu werden. Wir setzen also Zahnd
29#
發(fā)表于 2025-3-26 16:31:59 | 只看該作者
30#
發(fā)表于 2025-3-26 19:29:54 | 只看該作者
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