Titlebook: Deep Learning and Convolutional Neural Networks for Medical Image Computing; Precision Medicine, Le Lu,Yefeng Zheng,Lin Yang Book 2017 Spr

minutia

書目名稱Deep Learning and Convolutional Neural Networks for Medical Image Computing影響因子(影響力)




書目名稱Deep Learning and Convolutional Neural Networks for Medical Image Computing影響因子(影響力)學科排名




書目名稱Deep Learning and Convolutional Neural Networks for Medical Image Computing網絡公開度




書目名稱Deep Learning and Convolutional Neural Networks for Medical Image Computing網絡公開度學科排名




書目名稱Deep Learning and Convolutional Neural Networks for Medical Image Computing被引頻次




書目名稱Deep Learning and Convolutional Neural Networks for Medical Image Computing被引頻次學科排名




書目名稱Deep Learning and Convolutional Neural Networks for Medical Image Computing年度引用




書目名稱Deep Learning and Convolutional Neural Networks for Medical Image Computing年度引用學科排名




書目名稱Deep Learning and Convolutional Neural Networks for Medical Image Computing讀者反饋




書目名稱Deep Learning and Convolutional Neural Networks for Medical Image Computing讀者反饋學科排名

包租車船

Review of Deep Learning Methods in Mammography, Cardiovascular, and Microscopy Image Analysisnt role in disease detection and computer-aided decision-making. Machine learning techniques have powered many aspects in medical investigations and clinical practice. Recently, deep learning is emerging a leading machine learning tool in computer vision and begins attracting considerable attentions

小官

有抱負者

Aggressive

A Novel Cell Detection Method Using Deep Convolutional Neural Network and Maximum-Weight Independentocedures. In this chapter, we propose a novel algorithm for general cell detection problem: First, a set of cell detection candidates is generated using different algorithms with varying parameters. Second, each candidate is assigned a score by a trained deep convolutional neural network (DCNN). Fin

Reverie

Deep Learning for Histopathological Image Analysis: Towards Computerized Diagnosis on Cancerspathological tissue specimens. For a number of cancers, the clinical cancer grading system is highly correlated with the pathomic features of histologic primitives that appreciated from histopathological images. However, automated detection and segmentation of histologic primitives is pretty challen

Reverie

的染料

機警

Intact