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

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Delphine Allès,Pascal Vennessongh transfer learning. However, in this work, we propose a deep learning architecture that exploits fine-tuning and random initialization of weights in a multi-encoder with a single decoder network architecture.

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The European VC-Funded Startup Guideor a variety of problems?(Tan et?al. .; Chen et?al. .; Habibzadeh et?al. .; Putten et?al. .). Additionally, we incorporate multi-scale information in our approach by training models with different input image resolutions. This approach is taken since multi-scale approaches have been shown to be effe

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https://doi.org/10.1007/978-90-6704-743-2ysis (Wang et?al. .; Urban et?al. .; Shin et?al. .; Mohammed et?al. .). Colonoscopy, however, is a video-based modality and an endoscopist will always use the contextual information from previous frames to make an accurate decision about the potential presence of a polyp. Recent developments in sema

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The European Union’s Pivot to AfricaWireless Capsule Endoscopy (WCE) takes the form of a pill equipped with a CCD or CMOS sensor, two batteries, and a RF (radiofrequency) transmitter that enables the wireless identification of gastrointestinal abnormalities such as ulcers, blood, and polyps (Moglia et?al. .) with no need for hospitalization or sedation.

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