Recent advances on image edge detection: A comprehensive review
Edge detection is one of the most important and fundamental problems in the field of
computer vision and image processing. Edge contours extracted from images are widely …
computer vision and image processing. Edge contours extracted from images are widely …
The role of machine learning algorithms in materials science: A state of art review on industry 4.0
A Choudhury - Archives of Computational Methods in Engineering, 2021 - Springer
The 21st century has witnessed a rapid convergence of manufacturing technology, computer
science and information technology. This has led to a paradigm of 4.0. The hitherto known …
science and information technology. This has led to a paradigm of 4.0. The hitherto known …
Automatic detection of single ripe tomato on plant combining faster R-CNN and intuitionistic fuzzy set
C Hu, X Liu, Z Pan, P Li - IEEE Access, 2019 - ieeexplore.ieee.org
Fast and accurate detection of ripe tomatoes on plant, which replaces manual labor with a
robotic vision-based harvesting system, is a challenging task. Tomatoes in adjacent …
robotic vision-based harvesting system, is a challenging task. Tomatoes in adjacent …
Corner detection using multi-directional structure tensor with multiple scales
Corners are important features for image analysis and computer vision tasks. Local structure
tensors with multiple scales are widely used in intensity-based corner detectors. In this …
tensors with multiple scales are widely used in intensity-based corner detectors. In this …
Corner detection using second-order generalized Gaussian directional derivative representations
Corner detection is a critical component of many image analysis and image understanding
tasks, such as object recognition and image matching. Our research indicates that existing …
tasks, such as object recognition and image matching. Our research indicates that existing …
Flexible Gabor-based superpixel-level unsupervised LDA for hyperspectral image classification
Hyperspectral images encompass abundant information and provide unique characteristics
for material classification. However, the labeling of training samples can be challenging in …
for material classification. However, the labeling of training samples can be challenging in …
Geo‐information map** improves Canny edge detection method
Y Lijun, L Mengbo, W Tongxin, B Youfeng… - IET Image …, 2023 - Wiley Online Library
Aiming at the shortcomings of the current Canny edge detection method in terms of noise
removal, threshold setting, and edge recognition, this paper proposes a method for …
removal, threshold setting, and edge recognition, this paper proposes a method for …
Edge enhancement improves adversarial robustness in image classification
Imperceptible adversarial examples are capable of deceiving the deep neural networks with
high confidence. Recent studies show that it is particularly effective to control the attack …
high confidence. Recent studies show that it is particularly effective to control the attack …
Edge detection based on type-1 fuzzy logic and guided smoothening
Edge detection is an important phenomenon in computer vision. Edge detection is helpful in
contour detection and thus helpful in obtaining the important information. Edge detection …
contour detection and thus helpful in obtaining the important information. Edge detection …
A new edge detection approach via neutrosophy based on maximum norm entropy
It is a quite important step to find object edges in applications such as object recognition,
classification and segmentation. Therefore, the edge detection algorithm to be used directly …
classification and segmentation. Therefore, the edge detection algorithm to be used directly …