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Titlebook: Engineering Applications of Neural Networks; 19th International C Elias Pimenidis,Chrisina Jayne Conference proceedings 2018 Springer Natur

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樓主: 嬉戲
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發(fā)表于 2025-3-26 22:27:22 | 只看該作者
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發(fā)表于 2025-3-27 04:02:35 | 只看該作者
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發(fā)表于 2025-3-27 08:10:35 | 只看該作者
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發(fā)表于 2025-3-27 12:31:55 | 只看該作者
RR-FCN: Rotational Region-Based Fully Convolutional Networks for Object Detectiono not consider rotation, our region-based detector incorporates rotational invariance into networks efficiently and generate more appropriate features according to the rotation angle. Specifically, we propose component-sensitive feature maps, rotational RoI pooling and interceptive back propagation
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發(fā)表于 2025-3-27 17:10:32 | 只看該作者
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發(fā)表于 2025-3-27 19:20:55 | 只看該作者
Smoothing Regularized Extreme Learning?Machineever, in order to guarantee the convergence of the ELM algorithm, it initially requires a large number of hidden nodes. In addition, extreme learning machines have two drawbacks: over-fitting and the sensitivity of accuracy to the number of hidden nodes. The aim of this paper is to propose a new smo
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發(fā)表于 2025-3-27 23:32:28 | 只看該作者
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發(fā)表于 2025-3-28 03:07:17 | 只看該作者
Machine Learning with the Pong Game: A Case Studyroblems in Artificial Intelligence and Machine Learning: The goal is to create a self-playing agent that can compete against humans. In the past there have been introduced various Machine Learning approaches to solve this problem. This paper gives a summary of some notable techniques to creating a s
39#
發(fā)表于 2025-3-28 09:12:18 | 只看該作者
40#
發(fā)表于 2025-3-28 13:17:29 | 只看該作者
Network Intrusion Detection on Apache Spark with Machine Learning Algorithms to detect network attacks, and therefore requires more efficient and faster data processing methods to ensure network security. For this purpose, many intrusion detection systems have been developed and development works are continuing..This study; by comparing the performance of machine learning a
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