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Titlebook: Distributed Computing and Artificial Intelligence, 17th International Conference; Yucheng Dong,Enrique Herrera-Viedma,Sara Rodríguez Confe

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11#
發(fā)表于 2025-3-23 11:59:54 | 只看該作者
The European Economy in 100 Quotesuss the results of a preliminary experimental evaluation of our approach, trained with the dataset of all the submissions in the Italian National Online Judge, used to train students for the Italian Olympiads in Informatics.
12#
發(fā)表于 2025-3-23 15:51:40 | 只看該作者
13#
發(fā)表于 2025-3-23 18:44:13 | 只看該作者
14#
發(fā)表于 2025-3-24 00:52:59 | 只看該作者
SMARTSEC4COP: Smart Cyber-Grooming Detection Using Natural Language Processing and Convolutional Neith his development described. The model predicts a high number of false positives, therefore low precision and F-score, but a high 88.4% accuracy and 0.81 AUROC (Area under the Receiver Operating Characteristic).
15#
發(fā)表于 2025-3-24 02:37:09 | 只看該作者
16#
發(fā)表于 2025-3-24 06:45:08 | 只看該作者
Two Agent-Oriented Programming Approaches Checked Against a Coordination Problem,lemented multi-agent systems. In order to devise a quantitative comparison, the two considered languages are used to solve the same coordination problem, and obtained implementations are compared to discuss advantages and drawbacks of the two approaches.
17#
發(fā)表于 2025-3-24 13:52:19 | 只看該作者
A Lightweight Pedestrian Detection Model for Edge Computing Systems,mework can effectively reduce the miss rate of the YOLO-tiny detection model from 48.8% to 26.2% while achieving an inference speed of 31 frames per second (FPS) tested on the Caltech pedestrian dataset.
18#
發(fā)表于 2025-3-24 14:56:46 | 只看該作者
Collaborative Recommendations in Online Judges Using Autoencoder Neural Networks,uss the results of a preliminary experimental evaluation of our approach, trained with the dataset of all the submissions in the Italian National Online Judge, used to train students for the Italian Olympiads in Informatics.
19#
發(fā)表于 2025-3-24 22:55:02 | 只看該作者
20#
發(fā)表于 2025-3-25 01:03:07 | 只看該作者
Morphometric Characteristics in Discrete Domain for Brain Tumor Recognition, and High Grade (HG), in which the LG group is composed of grade I and II brain tumors, while the HG group is composed of grades III and IV brain tumors [.]. This paper focuses on the morphometric analysis of brain tumors and the study of the correlation of tumor shape with its degree of malignancy.
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