刚毅 发表于 2025-3-26 21:53:04
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Arnold Dashefsky,Ira M. Sheskin 3D ultrasound images. Evaluation metrics such as Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM) were utilized to measure the performance of the different filters. The experimental setup utilized ultrasound images from USOVA3D Training Set 1, yield斥责 发表于 2025-3-27 08:51:09
Ira M. Sheskin,Arnold Dashefsky dentists by identifying restorative and treatment needs for each tooth or patient, significantly enhancing dental care quality and efficiency. It showcased notable performance metrics: an accuracy of 89.14%, a precision of 95.84%, and a recall of 91.93%. Through advanced data augmentation and meticOvulation 发表于 2025-3-27 10:10:28
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Conference proceedings 2024the Department of Computer Applications, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Sikkim, India during April 29–30, 2024. The book presents diverse range of topics, including machine learning algorithms and models, deep learning and neural networks, computer vision and imagMURKY 发表于 2025-3-27 19:57:13
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Arnold Dashefsky,Ira M. Sheskinompressive strength across both the training and testing sets. Conversely, the ANN model exhibited slightly lower accuracy in the testing set. Sensitivity analysis indicated that concrete age was the most important parameter significantly influencing the GPC’s compressive strength, while curing time showed the least importance among the variables.embolus 发表于 2025-3-28 03:00:01
ViTaL: An Advanced Framework for Automated Plant Disease Identification in Leaf Images Using Visionute Module addresses low-memory configurations, ensuring practicality and affordability. This research contributes valuable insights and tools for early plant disease detection, potentially improving crop yields and food security.委托 发表于 2025-3-28 08:26:29
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