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Titlebook: Development and Analysis of Deep Learning Architectures; Witold Pedrycz,Shyi-Ming Chen Book 2020 Springer Nature Switzerland AG 2020 Compu

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發(fā)表于 2025-3-23 12:20:17 | 只看該作者
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978-3-030-31766-9Springer Nature Switzerland AG 2020
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發(fā)表于 2025-3-23 20:14:56 | 只看該作者
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發(fā)表于 2025-3-23 22:35:17 | 只看該作者
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發(fā)表于 2025-3-24 04:43:16 | 只看該作者
Development and Analysis of Deep Learning Architectures978-3-030-31764-5Series ISSN 1860-949X Series E-ISSN 1860-9503
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發(fā)表于 2025-3-24 09:07:09 | 只看該作者
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發(fā)表于 2025-3-24 14:31:23 | 只看該作者
Case Study: Deep Convolutional Networks in Healthcare,modified in accordance with the requirements of the problems. Through this chapter the most popular and up-to-date deep learning solutions to biomedical problems are discussed. Studies are analyzed according to problem characteristic, importance of solution, requirements and deep learning approaches
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發(fā)表于 2025-3-24 15:05:42 | 只看該作者
Deep Domain Adaptation for Regression,ssion applications using deep neural networks has not been explored in the literature. Our extensive empirical studies on two popular regression applications (age estimation and head pose estimation from images) depict the merit of our framework over competing baselines.
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發(fā)表于 2025-3-24 19:06:57 | 只看該作者
Deep Learning-Based Pedestrian Detection for Automated Driving: Achievements and Future Challenges, detection performance reaches human performance? As false detections can lead to hazardous situations in traffic scenarios, the expectations on the performance of artificial intelligence for advanced driver assistance systems and automated driving often go beyond human performance. Challenges are p
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發(fā)表于 2025-3-24 23:19:11 | 只看該作者
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