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- research-articleDecember 2022
Automated universal fractures detection in X-ray images based on deep learning approach
Multimedia Tools and Applications (MTAA), Volume 81, Issue 30Pages 44487–44503https://doi.org/10.1007/s11042-022-13287-zAbstractAt present, bone fracture is a common clinical disease, while the missed diagnosis or misdiagnosis of fracture is harmful to the recovery of patients. Fracture diagnosis often needs the X-ray image as an assistive tool and many fracture detection ...
- research-articleDecember 2022
CNN-based Hardhats Wearing Detection for On-site Monitoring
CSAE '22: Proceedings of the 6th International Conference on Computer Science and Application EngineeringArticle No.: 65, Pages 1–6https://doi.org/10.1145/3565387.3565452Hardhat is a class of indispensable equipment for workers to enter construction sites. Considering that many accidents occurred at the construction sites are related to the violations of rules by workers, detection of workers whether wearing hardhats is ...
- research-articleSeptember 2022
Pedestrian Detection in Crowded Scenes Based on Cascade R-CNN
ICCTA '22: Proceedings of the 2022 8th International Conference on Computer Technology ApplicationsPages 195–200https://doi.org/10.1145/3543712.3543720The occlusion in crowded scenes and the interference of similar objects in the background are one of the main reasons that lead to missed pedestrian detection. In response to this problem, an improved Cascade R-CNN pedestrian detection algorithm using ...
- research-articleApril 2022
Real-time high-precision pedestrian tracking: a detection–tracking–correction strategy based on improved SSD and Cascade R-CNN
Journal of Real-Time Image Processing (SPJRTIP), Volume 19, Issue 2Pages 287–302https://doi.org/10.1007/s11554-021-01183-yAbstractThe existing pedestrian tracking applications are challenging to balance real-time performance and accuracy. We propose a detection–tracking–correction strategy based on the improved single-shot multi-box detector (SSD), Deep-SORT, and the ...
- research-articleOctober 2021
Multiple attention encoded cascade R-CNN for scene text detection
Journal of Visual Communication and Image Representation (JVCIR), Volume 80, Issue Chttps://doi.org/10.1016/j.jvcir.2021.103261AbstractInspired by instance segmentation algorithms, researchers have proposed quantity of segmentation-based methods for text detection, achieving remarkable results on scene text with arbitrary orientation and large aspect ratios. Following ...
- research-articleJanuary 2021
Automatic image detection of multi-type surface defects on wind turbine blades based on cascade deep learning network
A safe operation protocol of the wind blades is a critical factor to ensure the stability of a wind turbine. Sensors are most commonly applied for defect detection on wind turbine blades (WTBs). However, due to the high cost and the sensitivity to ...
- research-articleOctober 2020
Pavement Damage Detection Based on Cascade R-CNN
CSAE '20: Proceedings of the 4th International Conference on Computer Science and Application EngineeringArticle No.: 154, Pages 1–5https://doi.org/10.1145/3424978.3425139In recent ten years, with the development of economy and the progress of science and technology, highway construction has gradually entered the stage of construction and maintenance. Among them, highway maintenance has become an important aspect of ...
- research-articleMay 2020
Improved Cascade R-CNN for Medical Images of Pulmonary Nodules Detection Combining Dilated HRNet
ICMLC '20: Proceedings of the 2020 12th International Conference on Machine Learning and ComputingPages 283–288https://doi.org/10.1145/3383972.3384070Using Computer-aided Diagnostic (CAD) to analyze medical images is currently a focused area, and deep learning is widely used in the detection of pulmonary nodules in medical imaging. Current detection algorithms are effective in detecting large ...