Recent advances and clinical applications of deep learning in medical image analysis
Deep learning has received extensive research interest in developing new medical image
processing algorithms, and deep learning based models have been remarkably successful …
processing algorithms, and deep learning based models have been remarkably successful …
A review of mathematical modeling, artificial intelligence and datasets used in the study, prediction and management of COVID-19
In the past few months, several works were published in regards to the dynamics and early
detection of COVID-19 via mathematical modeling and Artificial intelligence (AI). The aim of …
detection of COVID-19 via mathematical modeling and Artificial intelligence (AI). The aim of …
Segment anything
Abstract We introduce the Segment Anything (SA) project: a new task, model, and dataset for
image segmentation. Using our efficient model in a data collection loop, we built the largest …
image segmentation. Using our efficient model in a data collection loop, we built the largest …
Efficient test-time model adaptation without forgetting
Test-time adaptation provides an effective means of tackling the potential distribution shift
between model training and inference, by dynamically updating the model at test time. This …
between model training and inference, by dynamically updating the model at test time. This …
Zoom in and out: A mixed-scale triplet network for camouflaged object detection
The recently proposed camouflaged object detection (COD) attempts to segment objects that
are visually blended into their surroundings, which is extremely complex and difficult in real …
are visually blended into their surroundings, which is extremely complex and difficult in real …
Detecting camouflaged object in frequency domain
Camouflaged object detection (COD) aims to identify objects that are perfectly embedded in
their environment, which has various downstream applications in fields such as medicine …
their environment, which has various downstream applications in fields such as medicine …
Camouflaged object segmentation with distraction mining
Camouflaged object segmentation (COS) aims to identify objects that are" perfectly"
assimilate into their surroundings, which has a wide range of valuable applications. The key …
assimilate into their surroundings, which has a wide range of valuable applications. The key …
Concealed object detection
We present the first systematic study on concealed object detection (COD), which aims to
identify objects that are visually embedded in their background. The high intrinsic similarities …
identify objects that are visually embedded in their background. The high intrinsic similarities …
Pranet: Parallel reverse attention network for polyp segmentation
Colonoscopy is an effective technique for detecting colorectal polyps, which are highly
related to colorectal cancer. In clinical practice, segmenting polyps from colonoscopy …
related to colorectal cancer. In clinical practice, segmenting polyps from colonoscopy …
Simultaneously localize, segment and rank the camouflaged objects
Camouflage is a key defence mechanism across species that is critical to survival. Common
camouflage include background matching, imitating the color and pattern of the …
camouflage include background matching, imitating the color and pattern of the …