A survey of orthogonal moments for image representation: Theory, implementation, and evaluation
Image representation is an important topic in computer vision and pattern recognition. It
plays a fundamental role in a range of applications toward understanding visual contents …
plays a fundamental role in a range of applications toward understanding visual contents …
Delving deep into spatial pooling for squeeze-and-excitation networks
Abstract Squeeze-and-Excitation (SE) blocks have demonstrated significant accuracy gains
for state-of-the-art deep architectures by re-weighting channel-wise feature responses. The …
for state-of-the-art deep architectures by re-weighting channel-wise feature responses. The …
Wheat head counting in the wild by an augmented feature pyramid networks-based convolutional neural network
J Sun, K Yang, C Chen, J Shen, Y Yang, X Wu… - … and Electronics in …, 2022 - Elsevier
Wheat head counting plays an important role in crop yield estimation, which also meets
great challenges of high density, scale variation, and illumination difference. In this paper …
great challenges of high density, scale variation, and illumination difference. In this paper …
A survey on rotation invariance of orthogonal moments and transforms
The theory of moments and transforms is well established and widely applied to a number of
computer vision, pattern recognition and image processing applications. A sub-class of …
computer vision, pattern recognition and image processing applications. A sub-class of …
Blur invariants for image recognition
Blur is an image degradation that makes object recognition challenging. Restoration
approaches solve this problem via image deblurring, deep learning methods rely on the …
approaches solve this problem via image deblurring, deep learning methods rely on the …
IRDC-Net: Lightweight semantic segmentation network based on monocular camera for mobile robot navigation
Computer vision plays a significant role in mobile robot navigation due to the wealth of
information extracted from digital images. Mobile robots localize and move to the intended …
information extracted from digital images. Mobile robots localize and move to the intended …
Detection of deficiency of nutrients in grape leaves using deep network
It is quite natural that the crops may be affected from a number of diseases due to many
factors namely, change in climate, variations in environmental changings, deficiency of urea …
factors namely, change in climate, variations in environmental changings, deficiency of urea …
Interpretable deep learning architecture for gastrointestinal disease detection: A Tri-stage approach with PCA and XAI
GI abnormalities significantly increase mortality rates and impose considerable strain on
healthcare systems, underscoring the essential requirement for rapid detection, precise …
healthcare systems, underscoring the essential requirement for rapid detection, precise …
Hybrid Mobile Robot Path Planning Using Safe JBS-A* B Algorithm and Improved DWA Based on Monocular Camera
This paper addresses the formidable challenge of enabling autonomous navigation in
Mobile Robots (MRs), focusing on the development of advanced path planning strategies …
Mobile Robots (MRs), focusing on the development of advanced path planning strategies …
Progressive downsampling and adaptive guidance networks for dynamic scene deblurring
J Cui, W Li, W Guo, W Gong - Pattern Recognition, 2022 - Elsevier
The existing learning-based dynamic scene deblurring methods have made good progress
to some extent. However, these methods are usually based on multiscale strategy, which …
to some extent. However, these methods are usually based on multiscale strategy, which …