Titlebook: Computer-Aided Analysis of Gastrointestinal Videos; Jorge Bernal,Aymeric Histace Book 2021 Springer Nature Switzerland AG 2021 Computer Vi

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https://doi.org/10.1007/978-3-030-91363-2r can be shared between classification, segmentation, and object detection network. Based on this observation, we wonder if it is possible to combine those different parts and solve multiple tasks in a single network to save the cost of training multiple networks.

Engulf

Resistance

Clinical Context for Intelligent Systems in Colonoscopy.4 million new cases of CRC are diagnosed annually and the incidence rates are slightly higher in men than in women. The World Health Organization (WHO) reported a rate of mortality of . in 2018, as can be seen in Fig. ..

Rodent

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Insufficient

PAD416

Microgram

Multi-resolution Multi-task Network and Polyp Trackingr can be shared between classification, segmentation, and object detection network. Based on this observation, we wonder if it is possible to combine those different parts and solve multiple tasks in a single network to save the cost of training multiple networks.

Keshan-disease

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ResNetANA challenge. In some cases like RTC-ATC group ResNet-50 was used as a layer in Faster Convolutional Neural Network (FCNN) in order to build an automated recognition system to detect the presence of polyps in colonoscopy images.