famine 发表于 2025-3-30 10:38:34
Cognitive States Prediction with KNN and TomekLinks,e are a number of methods available for the cognitive states prediction. However imbalance in data is ultimately the challenge impacting the analysis performance. Here we use condensed nearest neighbors under-sampling technique to recover the class balance of training data before implementing k-near下级 发表于 2025-3-30 13:24:55
http://reply.papertrans.cn/63/6206/620570/620570_52.pngchampaign 发表于 2025-3-30 19:51:35
http://reply.papertrans.cn/63/6206/620570/620570_53.pngMisnomer 发表于 2025-3-30 22:39:21
http://reply.papertrans.cn/63/6206/620570/620570_54.pngCommentary 发表于 2025-3-31 00:59:36
http://reply.papertrans.cn/63/6206/620570/620570_55.png信任 发表于 2025-3-31 06:46:58
,Fake Face Detection with Separable Convolutions, a fake face embedded into an image can be perilous because it can deceive and mislead people, leading to false identification, impersonation, and even fraudulent activities. However, with great support from information technology, such fake images can be easily created by embedding and retouching tAngiogenesis 发表于 2025-3-31 09:38:50
A Classification System of Mammograms Based on Convolutional Neural Networks,nto three classes of Normal, Benign, and Malignant by increasing the training set. For training convolutional neural network models, we use 15,040 Vietnamese mammograms, which were collected and annotated by the radiologists of the Vietnam National Cancer Hospital. Our experiment was conducted withAnemia 发表于 2025-3-31 15:52:14
http://reply.papertrans.cn/63/6206/620570/620570_58.png首创精神 发表于 2025-3-31 20:53:57
http://reply.papertrans.cn/63/6206/620570/620570_59.pngALOFT 发表于 2025-4-1 00:28:58
Data Processing and Feature Engineering for Stock Price Trend Prediction,g stock prices using machine learning techniques and data mining has become a research topic that has captured the attention of the scientific community. Stock price prediction could greatly facilitate the investors’ appropriate decisions, improves profitability and hence decreases possible losses.