Evaluating the Single-Shot MultiBox Detector and YOLO Deep Learning Models for the Detection of Tomatoes in a Greenhouse
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Evaluating the Single-Shot MultiBox Detector and YOLO Deep Learning Models for the Detection of Tomatoes in a Greenhouse
Authors
Keywords
-
Journal
SENSORS
Volume 21, Issue 10, Pages 3569
Publisher
MDPI AG
Online
2021-05-20
DOI
10.3390/s21103569
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Detection, Quantification and Classification of Ripened Tomatoes using a Comparative Analysis of Image Processing and Machine Learning Methods: A case study
- (2020) Mohammed Karim et al. IET Image Processing
- The Open Images Dataset V4
- (2020) Alina Kuznetsova et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
- Detection of tomato organs based on convolutional neural network under the overlap and occlusion backgrounds
- (2020) Jun Sun et al. MACHINE VISION AND APPLICATIONS
- Intact Detection of Highly Occluded Immature Tomatoes on Plants Using Deep Learning Techniques
- (2020) Yue Mu et al. SENSORS
- YOLO-Tomato: A Robust Algorithm for Tomato Detection Based on YOLOv3
- (2020) Guoxu Liu et al. SENSORS
- Robust Cherry Tomatoes Detection Algorithm in Greenhouse Scene Based on SSD
- (2020) Ting Yuan et al. Agriculture-Basel
- Automatic Tomato and Peduncle Location System Based on Computer Vision for Use in Robotized Harvesting
- (2020) M. Benavides et al. Applied Sciences-Basel
- Automatic Recognition of Ripening Tomatoes by Combining Multi-Feature Fusion with a Bi-Layer Classification Strategy for Harvesting Robots
- (2019) Jingui Wu et al. SENSORS
- Cost–benefit analysis of tomato in soilless culture systems with saline water under greenhouse conditions
- (2019) José M Cámara‐Zapata et al. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
- Object Detection With Deep Learning: A Review
- (2019) Zhong-Qiu Zhao et al. IEEE Transactions on Neural Networks and Learning Systems
- Detecting tomatoes in greenhouse scenes by combining AdaBoost classifier and colour analysis
- (2016) Yuanshen Zhao et al. BIOSYSTEMS ENGINEERING
- Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion
- (2016) Yuanshen Zhao et al. SENSORS
- Harvesting Robots for High-value Crops: State-of-the-art Review and Challenges Ahead
- (2014) C. Wouter Bac et al. Journal of Field Robotics
- On Plant Detection of Intact Tomato Fruits Using Image Analysis and Machine Learning Methods
- (2014) Kyosuke Yamamoto et al. SENSORS
- Abscission Point Extraction for Ripe Tomato Harvesting Robots
- (2013) Lvwen Huang et al. INTELLIGENT AUTOMATION AND SOFT COMPUTING
- The Pascal Visual Object Classes (VOC) Challenge
- (2009) Mark Everingham et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started