Software bugs pose an ever-present concern for developers, and patching ...
To train the change detector, bi-temporal images taken at different time...
Labeling a large set of data is expensive. Active learning aims to tackl...
When the trained physician interprets medical images, they understand th...
Deep convolutional neural networks (CNNs) have shown state-of-the-art
pe...
Finding diseases from an X-ray image is an important yet highly challeng...
We propose Sequential Feature Filtering Classifier (FFC), a simple but
e...
Deep learning models often fail to maintain their performance on new tes...
We propose Convolutional Block Attention Module (CBAM), a simple yet
eff...
Recent advances in deep neural networks have been developed via architec...
Learning-based color enhancement approaches typically learn to map from ...