Search Results for author:
Found 10 papers, 7 papers with code
KDAS: Knowledge Distillation via Attention Supervision Framework for Polyp Segmentation
Polyp segmentation, a contentious issue in medical imaging, has seen numerous proposed methods aimed at improving the quality of segmented masks.
Ranked #15 on
Medical Image Segmentation
on CVC-ColonDB
ALGNet: Attention Light Graph Memory Network for Medical Recommendation System
In this paper, we propose ALGNet, a novel model that leverages light graph convolutional networks (LGCN) and augmentation memory networks (AMN) to enhance medication recommendation.
PGS: Pose-Guided Supervision for Mitigating Clothes-Changing in Person Re-Identification
Person Re-Identification (Re-ID) task seeks to enhance the tracking of multiple individuals by surveillance cameras.
Clothes Changing Person Re-Identification
Person Retrieval
+2
An objective validation of polyp and instrument segmentation methods in colonoscopy through Medico 2020 polyp segmentation and MedAI 2021 transparency challenges
Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps.
M^2UNet: MetaFormer Multi-scale Upsampling Network for Polyp Segmentation
Polyp segmentation has recently garnered significant attention, and multiple methods have been formulated to achieve commendable outcomes.
Meta-Polyp: a baseline for efficient Polyp segmentation
In 2022, Meta-Former was introduced as a new baseline for vision, which not only improved the performance of multi-task computer vision but also addressed the limitations of the Vision Transformer and CNN family backbones.
Ranked #3 on
Medical Image Segmentation
on CVC-ColonDB
Multi Kernel Positional Embedding ConvNeXt for Polyp Segmentation
Specifically, with the increase in cases, the diagnosis and identification need to be faster and more accurate for many patients; in endoscopic images, the segmentation task has been vital to helping the doctor identify the position of the polyps or the ache in the system correctly.
EfficientNet for Brain-Lesion classification
With the improvement of the architecture, there is a variety of methods that are proposed and achieve competitive scores.
Res-Dense Net for 3D Covid Chest CT-scan classification
In this paper, we propose a method that using a Stacking Deep Neural Network to detect the Covid 19 through the series of 3D CT-scans images .
Refined Deep Neural Network and U-Net for Polyps Segmentation
The Medico: Multimedia Task 2020 focuses on developing an efficient and accurate computer-aided diagnosis system for automatic segmentation [3].
