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Titlebook: Intelligent Information Processing IX; 10th IFIP TC 12 Inte Zhongzhi Shi,Eunika Mercier-Laurent,Jiuyong Li Conference proceedings 2018 IFIP

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樓主: cucumber
31#
發(fā)表于 2025-3-27 00:43:20 | 只看該作者
32#
發(fā)表于 2025-3-27 03:35:06 | 只看該作者
Multi-view Restricted Boltzmann Machines with Posterior Consistencynt modelling. However, the extensions of RBMs are rarely used in the field of multi-view learning. In this paper, we present a new multi-view RBM model, named as the RBM with posterior consistency, for multi-view classification. The RBM with posterior consistency computes multiple representations by
33#
發(fā)表于 2025-3-27 07:31:18 | 只看該作者
34#
發(fā)表于 2025-3-27 12:10:35 | 只看該作者
35#
發(fā)表于 2025-3-27 14:36:19 | 只看該作者
36#
發(fā)表于 2025-3-27 18:24:32 | 只看該作者
Automatic Driving Decision Algorithm Based on Multi-dimensional Deep Space-Time Networkiving was taken by the camera mounted on the vehicle. The images and the steering wheel angle and speed were collected as the model training input data. The multi frame vehicle image was pre-processed, the underlying feature image and the original image were used as the input of the multi-dimensiona
37#
發(fā)表于 2025-3-28 00:53:58 | 只看該作者
Tourist Attraction Recommendation Based on Knowledge Graphngkok city is constructed, and a tourist attraction recommendation model based on the knowledge graph is presented. Firstly, we collect tourism data in Bangkok and generate a tourist attraction knowledge graph by using the Neo4j tool. Then, by applying the network representation learning method Node
38#
發(fā)表于 2025-3-28 02:45:48 | 只看該作者
Elite Opposition-Based Selfish Herd Optimizern-based Selfish herd optimizer (EOSHO) has been applied to functions. Elite opposition-based learning is a commonly used strategy to improve the performance of metaheuristic algorithms. Elite opposition-based learning enhances the search space of the algorithm and the exploration of the algorithm. A
39#
發(fā)表于 2025-3-28 08:24:34 | 只看該作者
40#
發(fā)表于 2025-3-28 14:21:25 | 只看該作者
A Multi-agent Framework that Facilitates Decoupled Agent Functioningssistants. Intelligent agents focus on agents as entities that can act on environments. These agents demonstrate qualities such as autonomy, situational awareness, embodiment, and flexibility. A challenge faced is creating a mechanism for artificial intelligent agents to cross-communicate in a world
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