Deep learning
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...d Wide Web, public data repositories, and new high-performance computational capabilities that are mostly due to the new generation of graphics processing units (GPUs) needed to optimize these models [22]. Recent work has proven the deep-learning approach to be superior for tasks of classication and segmentation on histology whole-slide images, compared to the previous image processing techniques [48...
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...e grading. In the eld of articial intelligence, deep-learning computational models, which are composed of multiple processing layers, can learn numerous levels of abstraction for data representation [22]. These data abstractions have dramatically improved the state-of-the-art computer vision and visual object recog3 nition applications, and, in some cases, even exceed human performance [15]. Currentl...
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...cropping for an image, that image was discarded and replaced by a new image. 2.3. Training Architecture and Framework Deep-learning is strongly rooted in previously existing articial neural networks [22], although the construction of deep-learning models only recently became practical due to the availability of large amounts of training data and new high-performance GPU computational capabilities des...
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