Search Results - Rui-Feng Wang
- Showing 1 - 5 results of 5
-
1
Toward Efficient UAV-Based Small Object Detection: A Lightweight Network with Enhanced Feature Fusion by Xingyu Di, Kangning Cui, Rui-Feng Wang
Published 2025-06-01UAV-based small target detection is crucial in environmental monitoring, circuit detection, and related applications. However, UAV images often face challenges such as significant scale variation, dense small targets, high inter-class similarity, and intra-class diversity, which can lead to missed d...
Get full text
Article -
2
From sensors to insights: Technological trends in image-based high-throughput plant phenotyping by Rui-Feng Wang, Hao-Ran Qu, Wen-Hao Su
Published 2025-12-01With the rapid global population growth and increasing challenges in sustainable agriculture, high-throughput plant phenotyping (HTPP) has become a vital tool for advancing crop breeding and precision agriculture. This review provides a comprehensive overview of recent technological trends in image-...
Get full text
Article -
3
Effect of Different Mg Contents on the Microstructure and Properties of a New Zn-Mg Alloy by SHEN Yan, WANG Hong-xing, LI Rui-feng, WANG Jiang-xin
Published 2021-02-01In order to improve the properties of Zn-based alloys, a new Zn-Mg casting alloy was prepared by alloying technique. The effects of different Mg contents on the microstructure and properties of Zn-Mg casting alloys were investigated. Results showed that with the increase of the content of Mg, the gr...
Get full text
Article -
4
Research on Obtaining Pepper Phenotypic Parameters Based on Improved YOLOX Algorithm by Yukang Huo, Rui-Feng Wang, Chang-Tao Zhao, Pingfan Hu, Haihua Wang
Published 2025-07-01Pepper is a vital crop with extensive agricultural and industrial applications. Accurate phenotypic measurement, including plant height and stem diameter, is essential for assessing yield and quality, yet manual measurement is time-consuming and labor-intensive. This study proposes a deep learning-b...
Get full text
Article -
5
Resource-Efficient Cotton Network: A Lightweight Deep Learning Framework for Cotton Disease and Pest Classification by Zhengle Wang, Heng-Wei Zhang, Ying-Qiang Dai, Kangning Cui, Haihua Wang, Peng W. Chee, Rui-Feng Wang
Published 2025-07-01Cotton is the most widely cultivated natural fiber crop worldwide, yet it is highly susceptible to various diseases and pests that significantly compromise both yield and quality. To enable rapid and accurate diagnosis of cotton diseases and pests—thus supporting the development of effective control...
Get full text
Article