ArticleSensors (Basel, Switzerland)2019
Fruit Detection and Segmentation for AppleHarvesting Using Visual Sensor in Orchards.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 132 citations in OpenAlex.
- A Review of Orchard Canopy Perception Technologies for Variable-Rate Spraying.Sensors (Basel, Switzerland) · 2025Review
- A bibliometric review of deep learning in crop monitoring: trends, challenges, and future perspectives.Frontiers in artificial intelligence · 2025Review
- Deep Learning-Based Biomimetic Identification Method for Mask Wearing Standardization.Biomimetics (Basel, Switzerland) · 2024Article
- Research on Apple Recognition Algorithm in Complex Orchard Environment Based on Deep Learning.Sensors (Basel, Switzerland) · 2023Article
- A Survey of Robotic Harvesting Systems and Enabling Technologies.Journal of intelligent & robotic systems · 2023Review
- An improved YOLOv5s model for assessing apple graspability in automated harvesting scene.Frontiers in plant science · 2023Article
- Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic review.Frontiers in plant science · 2023Review
- SE-COTR: A Novel Fruit Segmentation Model for Green Apples Application in Complex Orchard.Plant phenomics (Washington, D.C.) · 2022Article
- Apple detection and instance segmentation in natural environments using an improved Mask Scoring R-CNN Model.Frontiers in plant science · 2022Article
- Applications of deep-learning approaches in horticultural research: a review.Horticulture research · 2021Review
- Developing a Modern Greenhouse Scientific Research Facility-A Case Study.Sensors (Basel, Switzerland) · 2021Article
- A Deep Learning-Based Vision System Combining Detection and Tracking for Fast On-Line Citrus Sorting.Frontiers in plant science · 2021Article
- Intelligent Fruit Yield Estimation for Orchards Using Deep Learning Based Semantic Segmentation Techniques-A Review.Frontiers in plant science · 2021Review
- Real-Time Fruit Recognition and Grasping Estimation for Robotic Apple Harvesting.Sensors (Basel, Switzerland) · 2020Article
- Toward Joint Acquisition-Annotation of Images with Egocentric Devices for a Lower-Cost Machine Learning Application to Apple Detection.Sensors (Basel, Switzerland) · 2020Article
- Recognition and Localization Methods for Vision-Based Fruit Picking Robots: A Review.Frontiers in plant science · 2020Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Autonomous harvesting shows a promising prospect in the future development of theagriculture industry, while the vision system is one of the most challenging components in theautonomous harvesting technologies. This work proposes a multi-function network to perform thereal-time detection and semantic segmentation of apples and branches in orchard environments byusing the visual sensor. The developed detection and segmentation network utilises the atrous spatialpyramid pooling and the gate feature pyramid network to enhance feature extraction ability of thenetwork. To improve the real-time computation performance of the network model, a lightweightbackbone network based on the residual network architecture is developed. From the experimentalresults, the detection and segmentation network with ResNet-101 backbone outperformed on thedetection and segmentation tasks, achieving an
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.