Image segmentation using deep learning: A survey
Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …
applications such as scene understanding, medical image analysis, robotic perception …
[HTML][HTML] Recent advances in image processing techniques for automated leaf pest and disease recognition–A review
LC Ngugi, M Abelwahab, M Abo-Zahhad - Information processing in …, 2021 - Elsevier
Fast and accurate plant disease detection is critical to increasing agricultural productivity in
a sustainable way. Traditionally, human experts have been relied upon to diagnose …
a sustainable way. Traditionally, human experts have been relied upon to diagnose …
Grand: Graph neural diffusion
B Chamberlain, J Rowbottom… - International …, 2021 - proceedings.mlr.press
Abstract We present Graph Neural Diffusion (GRAND) that approaches deep learning on
graphs as a continuous diffusion process and treats Graph Neural Networks (GNNs) as …
graphs as a continuous diffusion process and treats Graph Neural Networks (GNNs) as …
[HTML][HTML] Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl
Segmenting the nuclei of cells in microscopy images is often the first step in the quantitative
analysis of imaging data for biological and biomedical applications. Many bioimage analysis …
analysis of imaging data for biological and biomedical applications. Many bioimage analysis …
Face mask recognition system with YOLOV5 based on image recognition
G Yang, W Feng, J Jin, Q Lei, X Li… - 2020 IEEE 6th …, 2020 - ieeexplore.ieee.org
The rapid development of computer vision makes human-computer interaction possible and
has a wide application prospect. Since the discovery of the first case of COVID-19, the global …
has a wide application prospect. Since the discovery of the first case of COVID-19, the global …
WORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from CT image
Whole abdominal organ segmentation is important in diagnosing abdomen lesions,
radiotherapy, and follow-up. However, oncologists' delineating all abdominal organs from …
radiotherapy, and follow-up. However, oncologists' delineating all abdominal organs from …
[HTML][HTML] A curated mammography data set for use in computer-aided detection and diagnosis research
Published research results are difficult to replicate due to the lack of a standard evaluation
data set in the area of decision support systems in mammography; most computer-aided …
data set in the area of decision support systems in mammography; most computer-aided …
Blood vessel segmentation algorithms—review of methods, datasets and evaluation metrics
Background Blood vessel segmentation is a topic of high interest in medical image analysis
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …
Non-local deep features for salient object detection
Saliency detection aims to highlight the most relevant objects in an image. Methods using
conventional models struggle whenever salient objects are pictured on top of a cluttered …
conventional models struggle whenever salient objects are pictured on top of a cluttered …
Deep neural networks motivated by partial differential equations
L Ruthotto, E Haber - Journal of Mathematical Imaging and Vision, 2020 - Springer
Partial differential equations (PDEs) are indispensable for modeling many physical
phenomena and also commonly used for solving image processing tasks. In the latter area …
phenomena and also commonly used for solving image processing tasks. In the latter area …