Abstract: Fine-grained flower image classification (FGFIC) is challenging due to high similarities among species and variations within species, especially with limited training data. Existing genetic ...
Abstract: Convolutional Neural Networks (CNNs) dominate medical image classification, yet their “black box” nature limits understanding of their decision-making process. This study applies ...
As shown below, the inferred masks predicted by our segmentation model trained by the dataset appear similar to the ground truth masks, but they lack precision in certain areas. Humans in the Loop is ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback