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Titlebook: Intelligent Systems and Applications; Proceedings of the 2 Kohei Arai Conference proceedings 2023 The Editor(s) (if applicable) and The Aut

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樓主: quick-relievers
31#
發(fā)表于 2025-3-26 21:48:51 | 只看該作者
Leboh: An Android Mobile Application for Waste Classification Using TensorFlow Lite, authors develop an Android mobile application for waste classification using EfficientNet-Lite model from TensorFlow Lite. The model is trained and validated using a dataset containing 15,190 images from 11 classes: cardboard, paper, glass, metal, electronics, battery, plastic, textile, shoes, orga
32#
發(fā)表于 2025-3-27 02:19:01 | 只看該作者
33#
發(fā)表于 2025-3-27 08:08:40 | 只看該作者
34#
發(fā)表于 2025-3-27 12:52:20 | 只看該作者
Eigen Value Decomposition Utilizing Method for Data Hiding Based on Wavelet Multi-resolution Analysinvisibility of the hidden information by using eigen value decomposition as a preprocessing of the conventional wavelet Multi-Resolution Analysis (MRA) based method. In the proposed method, the information of the key image is protected by the existence of the eigenvector. That is, the key image inf
35#
發(fā)表于 2025-3-27 13:59:32 | 只看該作者
36#
發(fā)表于 2025-3-27 20:25:00 | 只看該作者
37#
發(fā)表于 2025-3-27 23:51:22 | 只看該作者
Detecting Complex Intrusion Attempts Using Hybrid Machine Learning Techniques, control of the arsenal is the Intrusion Detection System (IDS), which can automatically detect attacks and intrusion attempts. For the IDS to be effective, it needs to detect all kinds of attacks while not disturbing legitimate traffic by erroneously classifying them as attacks and affecting normal
38#
發(fā)表于 2025-3-28 04:18:05 | 只看該作者
Gauging Biases in Various Deep Learning AI Models,r research. Trustworthiness of AI results require very detailed and careful validation of the applied algorithms, as some errors and biases could reside deeply inside AI components, which might affect inclusiveness, equity, justice and irreversibly influence human lives. It is critical to detect the
39#
發(fā)表于 2025-3-28 07:23:06 | 只看該作者
Improving Meta-imitation Learning with Focused Task Embedding,eddings and perform the task specified by the given embedding. When the robot is tasked to perform a new, unseen task, it is given a single or just a few demonstrations, from which a new task embedding is obtained by generalizing from existing embeddings. Therefore, task encoding is key to the gener
40#
發(fā)表于 2025-3-28 14:16:50 | 只看該作者
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