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Titlebook: Intelligent Systems; 11th Brazilian Confe Jo?o Carlos Xavier-Junior,Ricardo Araújo Rios Conference proceedings 2022 The Editor(s) (if appli

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31#
發(fā)表于 2025-3-26 23:35:01 | 只看該作者
,Self-learning Methodology Based on?Degradation Estimation for?Underwater Image Enhancement,s an enhanced version of the input image. It is highlighted that the proposed algorithm requires only one image as input during the training. The results obtained using our method show its effectiveness of color preservation, color cast reduction, and contrast improvement.
32#
發(fā)表于 2025-3-27 03:37:03 | 只看該作者
33#
發(fā)表于 2025-3-27 09:20:57 | 只看該作者
34#
發(fā)表于 2025-3-27 09:59:47 | 只看該作者
,: A Corpus of?Literature in?Portuguese for?NLP,e ATG algorithms, which we have previously developed, behave when trained on this corpus, by using a human evaluation protocol where a mixture of automatically generated and . texts is classified, using four criteria: grammaticality, coherence, identification of context, and an adapted Turing test.
35#
發(fā)表于 2025-3-27 17:11:31 | 只看該作者
0302-9743 2022, which took place in Campinas, Brazil, in November/December 2022.?.The 89 papers presented in the proceedings were carefully reviewed and selected from 225 submissions. The conference deals with theoretical aspects and applications of artificial and computational intelligence..978-3-031-21688-
36#
發(fā)表于 2025-3-27 18:49:54 | 只看該作者
,A Sequential Recommender System with?Embeddings Based on?GraphSage Aggregators,ing and LSTM. We validated our proposal with the datasets: yoochoose, diginetica, aotm and 30music. The results indicate that, with the Mean aggregator, it is possible to reduce the execution time in all tested scenarios, maintaining the original effectiveness.
37#
發(fā)表于 2025-3-28 02:00:06 | 只看該作者
38#
發(fā)表于 2025-3-28 05:17:06 | 只看該作者
,BoVW-CAM: Visual Explanation from?Bag of?Visual Words, techniques for handcrafted features. This fact obscures the comparison between modern CNNs and classical methods for image classification. In this work, we present the BoVW-CAM that indicates the most important image regions for each prediction given by the BoVW technique. This way, we show a novel
39#
發(fā)表于 2025-3-28 09:33:09 | 只看該作者
,Using BERT to?Predict the?Brazilian Stock Market,cial time series, avoiding human intervention in the process. Our results are promising, with the developed approach overcoming the baselines Buy & Hold and Moving Average Crossover, considering both profitability and risk during the investment process.
40#
發(fā)表于 2025-3-28 13:22:22 | 只看該作者
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