SAR image edge detection: review and benchmark experiments
MJ Meester, AS Baslamisli - International Journal of Remote …, 2022 - Taylor & Francis
Edges are distinct geometric features crucial to higher level object detection and recognition
in remote-sensing processing, which is a key for surveillance and gathering up-to-date …
in remote-sensing processing, which is a key for surveillance and gathering up-to-date …
Local intensity order transformation for robust curvilinear object segmentation
Segmentation of curvilinear structures is important in many applications, such as retinal
blood vessel segmentation for early detection of vessel diseases and pavement crack …
blood vessel segmentation for early detection of vessel diseases and pavement crack …
Fast and accurate road crack detection based on adaptive cost-sensitive loss function
Numerous detection problems in computer vision, including road crack detection, suffer from
exceedingly foreground–background imbalance. Fortunately, modification of loss function …
exceedingly foreground–background imbalance. Fortunately, modification of loss function …
[HTML][HTML] CORF3D contour maps with application to Holstein cattle recognition from RGB and thermal images
Livestock management involves the monitoring of farm animals by tracking certain
physiological and phenotypical characteristics over time. In the dairy industry, for instance …
physiological and phenotypical characteristics over time. In the dairy industry, for instance …
A hybrid unsupervised approach for retinal vessel segmentation
Retinal vessel segmentation (RVS) is a significant source of useful information for
monitoring, identification, initial medication, and surgical development of ophthalmic …
monitoring, identification, initial medication, and surgical development of ophthalmic …
Enhanced robustness of convolutional networks with a push–pull inhibition layer
Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not
seen during training. In this paper, we propose a new layer for CNNs that increases their …
seen during training. In this paper, we propose a new layer for CNNs that increases their …
Multichannel Retinal Blood Vessel Segmentation Based on the Combination of Matched Filter and U‐Net Network
Aiming at the current problem of insufficient extraction of small retinal blood vessels, we
propose a retinal blood vessel segmentation algorithm that combines supervised learning …
propose a retinal blood vessel segmentation algorithm that combines supervised learning …
Pavement distress detection with deep learning using the orthoframes acquired by a mobile mapping system
The subject matter of this research article is automatic detection of pavement distress on
highway roads using computer vision algorithms. Specifically, deep learning convolutional …
highway roads using computer vision algorithms. Specifically, deep learning convolutional …
[HTML][HTML] A robust contour detection operator with combined push-pull inhibition and surround suppression
D Melotti, K Heimbach, A Rodríguez-Sánchez… - Information …, 2020 - Elsevier
Contour detection is a salient operation in many computer vision applications as it extracts
features that are important for distinguishing objects in scenes. It is believed to be a primary …
features that are important for distinguishing objects in scenes. It is believed to be a primary …
Local road area extraction in CSAR imagery exploiting improved curvilinear structure detector
Y Luo, D An, W Wang, L Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Road extraction is an important part of synthetic aperture radar (SAR) image interpretation.
In recent years, circular SAR (CSAR) has attracted extensive attention from researchers …
In recent years, circular SAR (CSAR) has attracted extensive attention from researchers …