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OSPINA ALARCON RICARDO
| Research Faculty of Agriculture Fundamental AgriScience Research Bioresource and Environmental Engineering | Assistant Professor |
| Institute for the Promotion of Business-Regional Collaboration | Assistant Professor |
| Institute for Academic Innovation | Assistant Professor |
Researcher basic information
■ Degree- Bachelor's in Electronics Engineering, Antioquia University (Colombia), Nov. 2007
- Master's in Environmental Resources Division, Hokkaido University, Sep. 2015
- Ph.D. in Agriculture, Hokkaido University, Sep. 2018
researchmap URLホームページURL■ Various IDs
Researcher number
- 20904220
- Bachelor's degree program, School of Agriculture
- Master's degree program, Graduate School of Agriculture
- Doctoral (PhD) degree program, Graduate School of Agriculture
Research activity information
■ Papers- Real-time work progress estimation based on GIS remote monitoring system for agricultural robot vehicles
Ricardo Ospina; Noboru Noguchi
Computers and Electronics in Agriculture, 234, 110313, 110313, Elsevier BV, Jul. 2025
Scientific journal - Smart Agriculture in Asia
Fahui Yuan; Ricardo Ospina; Anand Babu; Noboru Noguchi; Yong He; Yufei Liu
Plant Communications, May 2025, [Peer-reviewed]
English - Obstacle detection and avoidance system based on layered costmaps for robot tractors
Ricardo Ospina; Kota Itakura
Smart Agricultural Technology, 100973, 100973, Elsevier BV, Apr. 2025
Scientific journal - Deep Learning-Based Automated Cell Detection-Facilitated Meat Quality Evaluation
Hui Zheng; Nan Zhao; Saifei Xu; Jin He; Ricardo Ospina; Zhengjun Qiu; Yufei Liu
Foods, 13, 14, 2270, 2270, MDPI AG, 18 Jul. 2024
Scientific journal, Meat consumption is increasing globally. The safety and quality of meat are considered important issues for human health. During evaluations of meat quality and freshness, microbiological parameters are often analyzed. Counts of indicator cells can provide important references for meat quality. In order to eliminate the error of manual operation and improve detection efficiency, this paper proposed a Convolutional Neural Network (CNN) with a backbone called Detect-Cells-Rapidly-Net (DCRNet), which can identify and count stained cells automatically. The DCRNet replaces the single channel of residual blocks with the aggregated residual blocks to learn more features with fewer parameters. The DCRNet combines the deformable convolution network to fit flexible shapes of stained animal cells. The proposed CNN with DCRNet is self-adaptive to different resolutions of images. The experimental results indicate that the proposed CNN with DCRNet achieves an Average Precision of 81.2% and is better than traditional neural networks for this task. The difference between the results of the proposed method and manual counting is less than 0.5% of the total number of cells. The results indicate that DCRNet is a promising solution for cell detection and can be equipped in future meat quality monitoring systems. - Assessment of remote sensing in measuring soil parameters for precision tillage
Ishmael Nartey Amanor; Ospina Alarcon Ricardo; Noboru Noguchi
Journal of Terramechanics, 113-114, 100973, 100973, Elsevier BV, Jun. 2024
Scientific journal - A Vision-based Navigation System for an Agricultural Autonomous Tractor
Sristi Saha; Tsuyoshi Morita; Ricardo Ospina; Noboru Noguchi
IFAC-PapersOnLine, 55, 32, 48, 53, Elsevier BV, 2022
Scientific journal - Real-Time Disease Detection in Rice Fields in the Vietnamese Mekong Delta
Thanh Tinh NGUYEN; Ricardo OSPINA; Noboru NOGUCHI; Hiroshi OKAMOTO; Quang Hieu NGO
Environmental Control in Biology, 59, 2, 77, 85, Nov. 2021, [Peer-reviewed], [Last author], ［Internationally co-authored］, [International Magazine]
English, Scientific journal - Experiment of Integrated Technologies in Robotics, Network, and Computing for Smart Agriculture
Ryota ISHIBASHI; Takuma TSUBAKI; Shingo OKADA; Hiroshi YAMAMOTO; Takeshi KUWAHARA; Kenichi KAWAMURA; Keisuke WAKAO; Takatsune MORIYAMA; Ricardo OSPINA; Hiroshi OKAMOTO; Noboru NOGUCHI
IEICE Transactions on Communications, E105.B, Issue 4, 364, 378, Institute of Electronics, Information and Communications Engineers (IEICE), Nov. 2021, [Peer-reviewed], [Last author], [International Magazine]
English, Scientific journal - Utilization of Quasi-Zenith Satellite System for Navigation of a Robot Combine Harvester
Kannapat Udompant; Ricardo Ospina Alarcon; YongJoo Kim; Noboru Noguchi
Agronomy, 11, 3, 483, 483, MDPI AG, Mar. 2021, [Peer-reviewed], [Last author], ［Internationally co-authored］, [International Magazine]
Scientific journal, The purpose of this study is to evaluate the performance of a robot combine harvester by comparing the Centimeter Level Augmentation Service (CLAS) and the Multi-Global Navigation Satellite System (GNSS) Advanced Demonstration tool for Orbit and Clock Analysis (MADOCA) from the Quasi-Zenith Satellite System (QZSS) by using the Real Time Kinematic (RTK) positioning technique as a reference. The first section of this study evaluates the availability and the precision under static conditions by measuring the activation time, the reconnection time, and obtaining a Twice Distance Root Mean Square (2DRMS) of 0.04 m and 0.10 m, a Circular Error Probability (CEP) of 0.03 m and 0.08 m, and a Root Mean Square Error (RMSE) of 0.57 m and 0.54 m for the CLAS and MADOCA, respectively. The second section evaluates the accuracy under dynamic conditions by using a GNSS navigation-based combine harvester running in an experimental field. The results show that the RMSE of the lateral deviation is between 0.04 m and 0.69 m for MADOCA and between 0.03 m and 0.31 m for CLAS; which suggest that the CLAS positioning augmentation system can be utilized for the robot combine harvester if the user considers these accuracy and dynamic characteristics. - Development of phenotyping system using low altitude UAV imagery and deep learning
Suxing Lyu; Noboru Noguchi; Ricardo Ospina; Yuji Kishima
International Journal of Agricultural and Biological Engineering, 14, 1, 207, 215, Jan. 2021, [Peer-reviewed], [Last author], ［Internationally co-authored］, [International Magazine]
English, Scientific journal - Basic Research on a Field Scouting Robot Monitoring Crop Progress and Condition (Part 1)― High-accuracy Acquisition Method of Spectral Reflection ―
Yoshitomo YAMASAKI; Issei IKEDA; Ricardo OSPINA-ALARCON; Noboru NOGUCHI
Journal of the Japanese Society of Agricultural Machinery and Food Engineers, 83, 1, 37, 47, Jan. 2021, [Peer-reviewed], [Last author], [Domestic magazines]
English, Scientific journal - Improved inclination correction method applied to the guidance system of agricultural vehicles
Ricardo Ospina; Noboru Noguchi
International Journal of Agricultural and Biological Engineering, 13, 6, 183, 194, Nov. 2020, [Peer-reviewed], [Lead author], [International Magazine]
English, Scientific journal - Real-Time Weed Detection in Rice Fields in the Vietnamese Mekong Delta
Nguyễn Thành Tính; Ngô Quang Hiếu; Hiroshi OKAMOTO; Noboru NOGUCHI; Ricardo OSPINA
Journal of Japanese Society of Agricultural Machinery and Food Engineers 82(2020) 247-256, 82, 247, 256, May 2020, [Peer-reviewed], [Last author], ［Internationally co-authored］, [Domestic magazines]
English, Scientific journal - Simultaneous mapping and crop row detection by fusing data from wide angle and telephoto images
Ricardo OspinaNoboru Noguchi
Computers and Electronics in Agriculture, 162, 602, 612, Jul. 2019, [Peer-reviewed], [Lead author], [International Magazine]
English, Scientific journal - Alternative method to model an agricultural vehicle's tire parameters
Ricardo Ospina; Noboru Noguchi
Engineering in Agriculture, Environment and Food, 11, 1, 9, 18, Jan. 2018, [Peer-reviewed], [Lead author], [International Magazine]
English, Scientific journal - Determination of Tire Dynamic Properties: Application to an Agricultural Vehicle
Ricardo Ospina; Noboru Noguchi
Engineering in Agriculture, Environment and Food, 9, 1, 123, 130, Jan. 2016, [Peer-reviewed], [Lead author], [International Magazine]
English, Scientific journal
