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.

休闲

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.

影响

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.