14 papers · ranked by Valyu relevance
Zhuangwen Wu, Zhiping Wan, Dongdong Ge, Ludan Pan
Aiming at the difficulty in extracting the features of time-frequency images for the recognition of car engine sounds, we propose a method to recognize them based on a deformable feature map residual network. A deformable feature map residual block includes offset and convolutional layers. The offset layers shift the…
Jun Xiang, Ruru Pan, Weidong Gao, Kelvin K.L. Wong
The traditional manual defect detection method has low efficiency and is time-consuming and laborious. To address this issue, this paper proposed an automatic detection framework for fabric defect detection, which consists of a hardware system and detection algorithm. For the efficient and high-quality acquisition of…
Effat Sahragard, Hassan Farsi, Sajad Mohamadzadeh, Antonio Agudo
This paper presents a novel method for improving semantic segmentation performance in computer vision tasks. Our approach utilizes an enhanced UNet architecture that leverages an improved ResNet50 backbone. We replace the last layer of ResNet50 with deformable convolution to enhance feature representation.…
Chengming Rao, Zunhao Hu, QiMing Zhao, Min Shan + 2 more
One of the main challenges encountered in visual object detection is the multi-scale issue. Many approaches have been proposed to tackle this issue. In this article, we propose a novel neck that can perform effective fusion of multi-scale features for a single-stage object detector. This neck, named the deformable…
Jiarui Feng, Shenghui Zhang, Zhaoyu Zhai, Hongfeng Yu + 1 more
Asian soybean rust (ASR) is one of the major diseases that causes serious yield loss worldwide, even up to 80%. Early and accurate detection of ASR is critical to reduce economic losses. Hyperspectral imaging, combined with deep learning, has already been proved as a powerful tool to detect crop diseases. However…
Md. Foysal, A. B. M. Aowlad Hossain, Abdulsalam Yassine, M. Shamim Hossain
'M. Shamim Hossain'] The infectious coronavirus disease (COVID-19) has become a great threat to global human health. Timely and rapid detection of COVID-19 cases is very crucial to control its spreading through isolation measures as well as for proper treatment. Though the real-time reverse transcription-polymerase…
Yu Tian, Yanwen Liu, Baohang Lin, Peng Li + 1 more
To address the challenge of suboptimal object detection outcomes stemming from the deformability of marine flexible biological entities, this study introduces an algorithm tailored for detecting marine flexible biological targets. Initially, we compiled a dataset comprising marine flexible biological subjects and…
Xubo Li, Wenqing Wang, Lihua Sun, Bin Hu + 2 more
'Jincheng Zhang'] When performed by a person, aero-engine borescope inspection is easily influenced by individual experience and human factors that can lead to incorrect maintenance decisions, potentially resulting in serious disasters, as well as low efficiency. To address the absolute requirements of flight safety…
Zhuang Tian, Fan Yang, Lei Yang, Yunjie Wu + 3 more
'Peng Qian' 'Diogo Ribeiro'] Thoroughly and accurately identifying various defects on concrete surfaces is crucial to ensure structural safety and prolong service life. However, in actual engineering inspections, the varying shapes and complexities of concrete structural defects challenge the insufficient robustness…
Miao Zou, Xi Li, Quan Yuan, Tao Xiong + 5 more
'Zhenhua Xiao' 'Chaoran Cui' 'Xiaohui Han'] In this article, we propose an effective grasp detection network based on an improved deformable convolution and spatial feature center mechanism (DCSFC-Grasp) to precisely grasp unidentified objects. DCSFC-Grasp includes three key procedures as follows. First, improved…
Xin Zhong, Jing Qin, Mingyue Guo, Wangmeng Zuo + 1 more
Crowd counting is considered a challenging issue in computer vision. One of the most critical challenges in crowd counting is considering the impact of scale variations. Compared with other methods, better performance is achieved with CNN-based methods. However, given the limit of fixed geometric structures, the…
Lu Ji, Chao Chen, Chih-Chang Yu, Jian-Jiun Ding + 1 more
The aim of this study was to address the issue of significant performance degradation in existing defogging algorithms under extreme fog conditions. Traditional Taylor series-based deformable convolutions are limited by local approximation errors, while the heavy-tailed characteristics of the Cauchy distribution can…
Sijia Li, Furkat Sultonov, Jamshid Tursunboev, Jun-Hyun Park + 3 more
'Sangseok Yun' 'Jae-Mo Kang' 'Felipe Jiménez'] In this paper, we propose a novel two-stage transformer with GhostNet, which improves the performance of the small object detection task. Specifically, based on the original Deformable Transformers for End-to-End Object Detection (deformable DETR), we chose GhostNet as the…
Peng Zhou, Hong Fang, Gaochang Wu, Hugo Aguas
Defects in photovoltaic (PV) panels can significantly reduce the power generation efficiency of the system and may cause localized overheating due to uneven current distribution. Therefore, adopting precise pixel-level defect detection, i.e., defect segmentation, technology is essential to ensuring stable operation.…