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Titlebook: Intelligent Systems and Applications; Select Proceedings o Anand J. Kulkarni,Seyedali Mirjalili,Siba Kumar Ud Conference proceedings 2023 T

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21#
發(fā)表于 2025-3-25 05:14:28 | 只看該作者
1876-1100 he field.Covers the latest research in technological advance.This book comprises the proceedings of the International Conference on Intelligent Systems and Applications (ICISA 2022). The contents of this volume focus on novel and modified artificial intelligence and machine learning-based methods an
22#
發(fā)表于 2025-3-25 11:05:18 | 只看該作者
Artificial Intelligence for Satellite Image Processing: Application to Rainfall Estimationthe classification and estimation of rainfall intensities, satellite images were used for the implementation of these techniques. The training and validation was carried out by comparing the satellite images to the corresponding radar images. The results of these artificial intelligence-based techniques indicate very interesting performance.
23#
發(fā)表于 2025-3-25 14:22:41 | 只看該作者
24#
發(fā)表于 2025-3-25 19:05:28 | 只看該作者
Conference proceedings 2023inance, agriculture, food processing, crime prevention, smart homes, transportation, traffic control, and wildlife conservation, etc. This volume will prove a valuable resource for those in academia and industry.?.
25#
發(fā)表于 2025-3-25 23:37:58 | 只看該作者
26#
發(fā)表于 2025-3-26 02:22:49 | 只看該作者
27#
發(fā)表于 2025-3-26 08:14:18 | 只看該作者
Tomato Plant Leaf Disease Detection Using Inception V3ural Network). In terms of testing and validation accuracy, the intermediate results are presented. It is observed that the best training accuracy, 88.98% is obtained at the 10th epoch and the best validation accuracy, 85.80% is obtained at the 8th epoch. Lastly, we conclude our result.
28#
發(fā)表于 2025-3-26 11:30:50 | 只看該作者
Relationship LSTM Network for Prediction in Social Internet of Thingsces to the user in a given environment. The intelligence in the model using R-LSTM network is to determine the right data and predicting responding objects and relationship between the objects. The proposed work provides accuracy of 98.75% and loss of 0.37% to the SIoT smart environment.
29#
發(fā)表于 2025-3-26 15:34:06 | 只看該作者
Relationship-Based AES Security Model for Social Internet of Things this work, a security model is proposed that considers the relationship between devices and generates relationship keys. The standard 256-bit Advanced Encryption Standard algorithm is implemented along with a relationship key to perform encryption and decryption on the data generated.
30#
發(fā)表于 2025-3-26 19:34:34 | 只看該作者
Sanjivani Kulkarni,Shilpa Budhavale,Vaishali Langote
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