ArticleFrontiers in plant science2021
A Deep Learning-Based Vision System Combining Detection and Tracking for Fast On-Line Citrus Sorting.
Article in Frontiers in plant science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Postharvest Fruit Grading Technologies and Equipment: A Review.Foods (Basel, Switzerland) · 2026Review
- Deep learning based instance segmentation of mandarin fruit slices for precision assessment and morphological quantification.Scientific reports · 2026Article
- Development of a spontaneous disease diagnosis tool by executing an enhanced convolutional neural network model for citrus fruits and leaves.Scientific reports · 2026Article
- Artificial intelligence and biotechnology for smart storage: Quality and safety perspectives in horticultural produce.Current research in food science · 2026Review
- YOLOv10-LGDA: An Improved Algorithm for Defect Detection in Citrus Fruits Across Diverse Backgrounds.Plants (Basel, Switzerland) · 2025Article
- Maize seed appearance quality assessment based on improved Inception-ResNet.Frontiers in plant science · 2023Article
- A Novel Intelligent System for Dynamic Observation of Cotton Verticillium Wilt.Plant phenomics (Washington, D.C.) · 2023Article
- Predicting and Visualizing Citrus Color Transformation Using a Deep Mask-Guided Generative Network.Plant phenomics (Washington, D.C.) · 2023Article
- Automatic Classification Service System for Citrus Pest Recognition Based on Deep Learning.Sensors (Basel, Switzerland) · 2022Article
- Application of Convolutional Neural Network-Based Detection Methods in Fresh Fruit Production: A Comprehensive Review.Frontiers in plant science · 2022Review
- Citrus disease detection using convolution neural network generated features and Softmax classifier on hyperspectral image data.Frontiers in plant science · 2022Article
- Non-destructive Storage Time Prediction of Newhall Navel Oranges Based on the Characteristics of Rind Oil Glands.Frontiers in plant science · 2022Article
- Tobacco shred varieties classification using Multi-Scale-X-ResNet network and machine vision.Frontiers in plant science · 2022Article
- Surface Defect Detection of Cabbage Based on Curvature Features of 3D Point Cloud.Frontiers in plant science · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Defective citrus fruits are manually sorted at the moment, which is a time-consuming and cost-expensive process with unsatisfactory accuracy. In this paper, we introduce a deep learning-based vision system implemented on a citrus processing line for fast on-line sorting. For the citrus fruits rotating randomly on the conveyor, a convolutional neural network-based detector was developed to detect and temporarily classify the defective ones, and a SORT algorithm-based tracker was adopted to record the classification information along their paths. The true categories of the citrus fruits were identified through the tracked historical information, resulting in high detection precision of 93.6%. Moreover, the linear Kalman filter model was applied to predict the future path of the fruits, which can be used to guide the robot arms to pick out the defective ones. Ultimately, this research presents a practical solution to realize on-line citrus sorting featuring low costs, high efficiency, and accuracy.
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