Topological Signal Processing (TSP) utilizes simplicial complexes to mod...
Previous raw image-based low-light image enhancement methods predominant...
Low-light image enhancement task is essential yet challenging as it is
i...
The examination of blood samples at a microscopic level plays a fundamen...
While raw images have distinct advantages over sRGB images, e.g., linear...
Plug-and-play Image Restoration (IR) has been widely recognized as a fle...
Staining is critical to cell imaging and medical diagnosis, which is
exp...
Recognizing the types of white blood cells (WBCs) in microscopic images ...
While raw images exhibit advantages over sRGB images (e.g., linearity an...
A protector is placed in front of the camera lens for mobile devices to ...
Recent deep learning methods have achieved promising results in image sh...
While deep learning succeeds in a wide range of tasks, it highly depends...
Active learning promises to improve annotation efficiency by iteratively...
We propose a manager-worker framework based on deep reinforcement learni...
Image restoration schemes based on the pre-trained deep models have rece...
Children's cognitive abilities are sometimes cited as AI benchmarks. How...
Images captured in the low-light condition suffer from low visibility an...
One of the fundamental challenges in image restoration is denoising, whe...
Deep learning models are vulnerable to adversarial examples and make
inc...
Learning the generalizable feature representation is critical for few-sh...
To align advanced artificial intelligence (AI) with human values and pro...
Low-light image enhancement (LLIE) is a pervasive yet challenging proble...
State-of-the-art image denoisers exploit various types of deep neural
ne...
Recent image classification algorithms, by learning deep features from
l...
StyleGAN is one of the state-of-the-art image generators which is well-k...
Adversarial training is one of the most effective approaches defending
a...
Low-dimensional embeddings for data from disparate sources play critical...
Deep learning models are shown to be vulnerable to adversarial examples....
Deep neural networks have been widely applied and achieved great success...
Graph Neural Networks (GNN) has demonstrated the superior performance in...
Constructing effective image priors is critical to solving ill-posed inv...
Moving object detection is critical for automated video analysis in many...
Recent works that utilized deep models have achieved superior results in...
Image prior modeling is the key issue in image recovery, computational
i...
Several recent works discussed application-driven image restoration neur...
Magnetic resonance imaging (MRI) is widely used in clinical practice for...
Image denoising and high-level vision tasks are usually handled independ...
Recent works on adaptive sparse and on low-rank signal modeling have
dem...
Many classic methods have shown non-local self-similarity in natural ima...
Techniques exploiting the sparsity of images in a transform domain have ...
Conventionally, image denoising and high-level vision tasks are handled
...
Ground-based whole sky cameras have opened up new opportunities for
moni...
Many images, of natural or man-made scenes often contain Similar but Gen...