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Titlebook: Artificial Intelligence and Machine Learning; First International Hai Jin,Yi Pan,Jianfeng Lu Conference proceedings 2024 The Editor(s) (if

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樓主: CLOG
51#
發(fā)表于 2025-3-30 12:05:31 | 只看該作者
Regularized DNN Based Adaptive Compensation Algorithm for Gateway Power Meter in Ultra-High Voltage ultra-high voltage substation energy meter based on regularized deep neural networks (DNN) to enhance metering accuracy. Finally, the effectiveness of this algorithm is validated through simulation experiments.
52#
發(fā)表于 2025-3-30 13:54:54 | 只看該作者
53#
發(fā)表于 2025-3-30 19:09:35 | 只看該作者
Conference proceedings 2024ovember 2023.. The 85 full papers presented were carefully reviewed and selected from 428 submissions.?The papers are clustered in parts on: Artificial Intelligence and Machine Learning; Data Security and information Security; Computer Networks and IoT. The papers present recent research and develop
54#
發(fā)表于 2025-3-30 21:59:18 | 只看該作者
55#
發(fā)表于 2025-3-31 01:24:40 | 只看該作者
Allison Daniel Anders,George W. Noblitits own prototype, to represent O-class entities more accurately. It also optimizes the distribution of entities in the feature space for better entity classification. Experimental results show that the model proposed in this paper improves performance on mainstream datasets.
56#
發(fā)表于 2025-3-31 06:00:33 | 只看該作者
A Review of Relationship Extraction Based on Deep Learning,elation extraction tasks, including data sparsity, long-distance dependency, and outlooks new techniques like weakly supervised relation extraction. This paper provides a systematic overview of deep learning techniques for relation extraction, aiming to facilitate further research in this field.
57#
發(fā)表于 2025-3-31 09:50:27 | 只看該作者
Enhanced Prototypical Network for Few-Shot Named Entity Recognition,its own prototype, to represent O-class entities more accurately. It also optimizes the distribution of entities in the feature space for better entity classification. Experimental results show that the model proposed in this paper improves performance on mainstream datasets.
58#
發(fā)表于 2025-3-31 15:20:20 | 只看該作者
1865-0929 hina, in November 2023.. The 85 full papers presented were carefully reviewed and selected from 428 submissions.?The papers are clustered in parts on: Artificial Intelligence and Machine Learning; Data Security and information Security; Computer Networks and IoT. The papers present recent research a
59#
發(fā)表于 2025-3-31 20:54:50 | 只看該作者
,Automated Detection and?Recognition of?Wild Dolphin Behaviors Using Deep Learning,his data achieved high levels of accuracy (0.99 for exiting, 0.92 for wandering, and 0.88 for entering). The method is the first to achieve visual action recognition of dol-phins behavior, opening new possibilities for using large datasets in dolphins research.
60#
發(fā)表于 2025-4-1 01:39:32 | 只看該作者
1865-0929 nd developments in artificial intelligence and its applications in machine learning, natural language processing, computer vision, robotics, and ethical considerations..978-981-97-1276-2978-981-97-1277-9Series ISSN 1865-0929 Series E-ISSN 1865-0937
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