Bayesian optimization (BO) has contributed greatly to improving model
pe...
Cell detection is a fundamental task in computational pathology that can...
Computational pathology can lead to saving human lives, but models are
a...
Despite the evolution of Convolutional Neural Networks (CNNs), their
per...
Annotating tens or hundreds of tiny objects in a given image is laboriou...
Finding diseases from an X-ray image is an important yet highly challeng...
Deep learning models often fail to maintain their performance on new tes...
Dashboard cameras capture a tremendous amount of driving scene video eac...
Nuclei segmentation is one of the important tasks for whole slide image
...
The performance of deep neural networks improves with more annotated dat...
Learning-based color enhancement approaches typically learn to map from ...
In this paper, we explore methods of complicating self-supervised tasks ...
Weakly supervised semantic segmentation and localiza- tion have a proble...
A dominant paradigm for deep learning based object detection relies on a...
We present an image-conditional image generation model. The model transf...
We present a novel detection method using a deep convolutional neural ne...
Compared to image representation based on low-level local descriptors, d...