Hardnet-mseg: A simple encoder-decoder polyp segmentation neural network that achieves over 0.9 mean dice and 86 fps

CH Huang, HY Wu, YL Lin - arXiv preprint arXiv:2101.07172, 2021 - arxiv.org
We propose a new convolution neural network called HarDNet-MSEG for polyp
segmentation. It achieves SOTA in both accuracy and inference speed on five popular …

[HTML][HTML] Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy

S Ali, M Dmitrieva, N Ghatwary, S Bano, G Polat… - Medical image …, 2021 - Elsevier
Abstract The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative
to address eminent problems in developing reliable computer aided detection and diagnosis …

Depth-wise Squeeze and Excitation Block-based Efficient-Unet model for surface defect detection

H Üzen, M Turkoglu, M Aslan, D Hanbay - The Visual Computer, 2023 - Springer
Detection of surface defects in manufacturing systems is crucial for product quality. Detection
of surface defects with high accuracy can prevent financial and time losses. Recently, efforts …

[HTML][HTML] U-Net model with transfer learning model as a backbone for segmentation of gastrointestinal tract

N Sharma, S Gupta, D Koundal, S Alyami, H Alshahrani… - Bioengineering, 2023 - mdpi.com
The human gastrointestinal (GI) tract is an important part of the body. According to World
Health Organization (WHO) research, GI tract infections kill 1.8 million people each year. In …

Cross-dimensional transfer learning in medical image segmentation with deep learning

H Messaoudi, A Belaid, DB Salem, PH Conze - Medical image analysis, 2023 - Elsevier
Over the last decade, convolutional neural networks have emerged and advanced the state-
of-the-art in various image analysis and computer vision applications. The performance of …

Rethinking exemplars for continual semantic segmentation in endoscopy scenes: Entropy-based mini-batch pseudo-replay

G Wang, L Bai, Y Wu, T Chen, H Ren - Computers in Biology and Medicine, 2023 - Elsevier
Endoscopy is a widely used technique for the early detection of diseases or robotic-assisted
minimally invasive surgery (RMIS). Numerous deep learning (DL)-based research works …

FAPN: Feature augmented pyramid network for polyp segmentation

Y Su, J Cheng, M Yi, H Liu - Biomedical Signal Processing and Control, 2022 - Elsevier
Accurate polyp segmentation during colonoscopy examinations can help the clinicians
accurately locate polyp areas for further diagnosis or surgeries and thereby decrease the …

Polyp segmentation network with hybrid channel-spatial attention and pyramid global context guided feature fusion

X Huang, L Zhuo, H Zhang, Y Yang, X Li… - … Medical Imaging and …, 2022 - Elsevier
In clinical practice, automatic polyp segmentation from colonoscopy images is an effective
assistant manner in the early detection and prevention of colorectal cancer. This paper …

A novel weighted ensemble transferred U-net based model (WETUM) for post-earthquake building damage assessment from UAV data: A comparison of deep …

E Khankeshizadeh, A Mohammadzadeh… - … on Geoscience and …, 2024 - ieeexplore.ieee.org
Nowadays, unmanned aerial vehicle (UAV) remote sensing (RS) data are key operational
sources used to produce a reliable building damage map (BDM), which is of great …

[HTML][HTML] Semantic segmentation of plant roots from RGB (mini-) rhizotron images—generalisation potential and false positives of established methods and advanced …

P Baykalov, B Bussmann, R Nair, AG Smith, G Bodner… - Plant Methods, 2023 - Springer
Background Manual analysis of (mini-) rhizotron (MR) images is tedious. Several methods
have been proposed for semantic root segmentation based on homogeneous, single-source …