In the real world, image degradations caused by rain often exhibit a
com...
Whole slide image (WSI) classification is an essential task in computati...
Recently, deep learning methods have been widely used for tumor segmenta...
In the treatment of ovarian cancer, precise residual disease prediction ...
Deep learning (DL) has proven highly effective for ultrasound-based
comp...
The multi-scale information among the whole slide images (WSIs) is essen...
Multi-modal Magnetic Resonance Imaging (MRI) plays an important role in
...
Fast and accurate MRI reconstruction is a key concern in modern clinical...
Varicolored haze caused by chromatic casts poses haze removal and depth
...
Although Convolutional Neural Networks (CNN) have made good progress in ...
Deep learning (DL)-based tomographic SAR imaging algorithms are graduall...
Benefiting from a relatively larger aperture's angle, and in combination...
This work focuses on 3D Radar imaging inverse problems. Current methods
...
With the booming of Convolutional Neural Networks (CNNs), CNNs such as V...
Single image desnowing is a common yet challenging task. The complex sno...
Transformer has been widely used in histopathology whole slide image (WS...
Local representation learning has been a key challenge to promote the
pe...
Computer-aided diagnosis (CAD) can help pathologists improve diagnostic
...
Convolutional neural networks (CNNs) and their variants have been
succes...
Real-world recommender system needs to be regularly retrained to keep wi...
Ubiquitous personalized recommender systems are built to achieve two
see...
Over-parameterized deep networks trained using gradient-based optimizers...
The thick-slice magnetic resonance (MR) images are often structurally bl...
Task-driven semantic video/image coding has drawn considerable attention...
The ongoing global pandemic of Coronavirus Disease 2019 (COVID-19) has p...
Content-based histopathological image retrieval (CBHIR) has become popul...
Pedestrian trajectory prediction for surveillance video is one of the
im...
Deep learning can promote the mammography-based computer-aided diagnosis...
Quantitative Susceptibility Mapping (QSM) is a new phase-based technique...
This letter proposes a novel Balance Scene Learning Mechanism (BSLM) for...
Practical large-scale recommender systems usually contain thousands of
f...
The pandemic of coronavirus disease 2019 (COVID-19) is spreading all ove...
Accelerating the inference speed of CNNs is critical to their deployment...
This paper reviews the AIM 2019 challenge on constrained example-based s...
Rapid growing intelligent applications require optimized bit allocation ...
Deep learning has been successfully applied to the single-image
super-re...
In the NIPS 2017 Learning to Run challenge, participants were tasked wit...