… [39] used a fully automatic segmentation method combined with adaptive and reasoning …
and fuzzy region growing to automatically segment brain tumor tissues on MR images. Xia et al. …

… Support vector machine (SVM), convolutional neural network (CNN), and deep learning (DL)
models are the most widely used AI classification techniques for AD detection and …

… We consider using two standard regression methods: l2-regularization and Support Vector
… Latent support vector machine for sign language recognition with Kinect. In Proc. the …

… tumor CT images from three aspects: datasets, evaluation indicators and algorithms. First,
we introduce common databases of liver tumors … brain tumor image segmentation. Journal of …

… automatic and precise breast mass identification. Method In this work,we compared different
image segmentation … (structured support vector machine)的深度学习特征的第2和第3模型. …

… (multi-layer perceptron, MLP),支持向量机 (support vector machine, SVM)等[3]均属于ML, 其中
… cell lung cancer prognosis by fully automated microscopic pathology image features[J]. Nat …

… imagery based on incremental support vector data description. … using an optimized support
vector data description method. In: Proceedings of the 3rd Workshop on Hyperspectral Image …

… have been carried out using computerdominated and artificial auxiliary technology (
Homer,2004; Friedl,2010) . But these have failed to achieve full automation ( being limited by the …

… to the point that imaging specialists can automatically detect vascular calcification. Artificial
intelligence can contribute to the successful development of X-ray imaging in the future. …

… In this work, we considered fully automated procedure for brain extraction. Nevertheless,
softwares of both BET and HWA provide options for the manual specification of …