Titlebook: Distributed Computing and Artificial Intelligence, 17th International Conference; Yucheng Dong,Enrique Herrera-Viedma,Sara Rodríguez Confe

moribund

Classification of Chest Diseases Using Deep Learning, as object recognition, detection and segmentation over approaches based on obtaining the characteristics of the image by hand [.]. This article presents a novel method for the classification of chest diseases in the standard and widely used data set ChestX-ray8, which contains more than 100,000 front view images with 8 diseases.

certain

braggadocio

emulsify

https://doi.org/10.1007/978-3-031-68819-5cy) in order to assess the confidence in the value of a feature, and to select the values that are most plausible. We show that it enables to handle various difficult situations (attacks, failures, etc.), by maintaining a coherent scene at any time despite possibly major defects.

休閑

intoxicate

Erik Gawel,Sebastian Strunz,Alexandra Purkus derived from the parallel execution of both algorithms, calculating the average of 20 repetitions on a small architecture of 6 physical cores and 12 ones with multi-threading, show that accelerations of up?to 21 times can be achieved with NFL and up?to 13 times with RNFLS.

chronology

Albert Hoffrichter,Thorsten Beckersataset. For the semantic segmentation method, we used a model called DeepLabv3+. The effectiveness of our experiment is confirmed by computer simulations showing the segmentation result of test images from four-scene comics.

影響

女歌星

Emg827

Analysis of Partial Semantic Segmentation for Images of Four-Scene Comics,ataset. For the semantic segmentation method, we used a model called DeepLabv3+. The effectiveness of our experiment is confirmed by computer simulations showing the segmentation result of test images from four-scene comics.