expeditious
发表于 2025-3-25 06:46:49
Seth C. Anderson,Jeffery A. Bornprevented only if it is detected at an early stage. Early diagnosis of glaucoma is possible by measuring the level of intra-ocular pressure (IOP) and the amount of neuro-retinal rim (NRR) area loss. The diagnosis accuracy depends on the experience and domain knowledge of the ophthalmologist. Hence,
潜移默化
发表于 2025-3-25 09:30:24
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MIR
发表于 2025-3-25 12:27:42
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SEED
发表于 2025-3-25 18:43:14
978-981-10-8568-0Springer Nature Singapore Pte Ltd. 2018
恸哭
发表于 2025-3-25 20:37:36
2194-5357 data mining.Serves as a good reference material for future w.The Volume of “.Advances in Machine Learning and Data Science - Recent Achievements and Research Directives.” constitutes the proceedings of First International Conference on Latest Advances in Machine Learning and Data Science (LAMDA 2017
NORM
发表于 2025-3-26 00:30:33
Monitors in Closed-Circuit Anaesthesiasirable to design appropriate RBFNN which balance between simplicity and accuracy. In the literature, many approaches are proposed for reducing the neurons in the RBFNN hidden layer. In this paper, a comprehensive survey is performed on hidden layer reduction techniques with respect to Pima Indians Diabetes (PID) dataset.
Acetabulum
发表于 2025-3-26 05:35:38
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Lamina
发表于 2025-3-26 10:28:33
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Cerumen
发表于 2025-3-26 14:05:09
https://doi.org/10.1007/978-1-4471-5140-1ccelerate the training and testing phases of machine learning problems. We also emphasize to demonstrate the efficiency achieved via predicting airline delay through both the sequential as well as CUDA-based parallel approach. Experimental results show that the proposed parallel CUDA approach outperforms in terms of its execution time.
圆木可阻碍
发表于 2025-3-26 19:57:17
Seth C. Anderson,Jeffery A. Borngram of oriented gradients (HOG) feature extraction and GCV-based regularized ELM are applied. Experimental results on facial expression database JAFFE demonstrate promising performance which outperforms the other two classifiers, namely support vector machine (SVM) and k-nearest neighbor (KNN).