|
|
|
|
|
Yasutake Koishi, Shuichi Ishida, Tatsuo Tabaru and Hiroyuki Miyamoto
Transfer learning aims for high accuracy by applying knowledge of source domains for which data collection is easy in order to target domains where data collection is difficult, and has attracted attention in recent years because of its significant poten...
ver más
|
|
|
|
|
|
|
|
|
|
|
Alexander Buslaev, Vladimir I. Iglovikov, Eugene Khvedchenya, Alex Parinov, Mikhail Druzhinin and Alexandr A. Kalinin
Data augmentation is a commonly used technique for increasing both the size and the diversity of labeled training sets by leveraging input transformations that preserve corresponding output labels. In computer vision, image augmentations have become a co...
ver más
|
|
|
|
|
|
|
|
|
|
|
Donghuan Wang, Hong Xiao and Shengqin Huang
Radiographic testing is generally used in the quality management of aeroengine turbine blades. Traditional radiographic testing is critically dependent on artificially detecting professional inspectors. Thus, it sometimes tends to be error-prone and time...
ver más
|
|
|
|
|
|
|
|
|
|
|
Haixia Qi, Yu Liang, Quanchen Ding and Jun Zou
Peanut is an important food crop, and diseases of its leaves can directly reduce its yield and quality. In order to solve the problem of automatic identification of peanut-leaf diseases, this paper uses a traditional machine-learning method to ensemble t...
ver más
|
|
|
|
|
|