Image processing and artificial intelligence for apple detection and localization: A comprehensive review

Computer Science Review, Год журнала: 2024, Номер 54, С. 100690 - 100690

Опубликована: Ноя. 1, 2024

Язык: Английский

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Development and evaluation of a dual-arm robotic apple harvesting system

Computers and Electronics in Agriculture, Год журнала: 2024, Номер 227, С. 109586 - 109586

Опубликована: Ноя. 14, 2024

Язык: Английский

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Advances in Object Detection and Localization Techniques for Fruit Harvesting Robots

Agronomy, Год журнала: 2025, Номер 15(1), С. 145 - 145

Опубликована: Янв. 9, 2025

Due to the short time, high labor intensity and workload of fruit vegetable harvesting, robotic harvesting instead manual operations is future. The accuracy object detection location directly related picking efficiency, quality speed fruit-harvesting robots. Because its low recognition accuracy, slow poor localization traditional algorithm cannot meet requirements automatic-harvesting increasingly evolving powerful deep learning technology can effectively solve above problems has been widely used in last few years. This work systematically summarizes analyzes about 120 literatures on three-dimensional positioning algorithms robots over 10 years, reviews several significant methods. difficulties challenges faced by current are proposed from aspects lack large-scale high-quality datasets, complexity agricultural environment, etc. In response challenges, corresponding solutions future development trends constructively proposed. Future research technological should first these using weakly supervised learning, efficient lightweight model construction, multisensor fusion so on.

Язык: Английский

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MetaFruit meets foundation models: Leveraging a comprehensive multi-fruit dataset for advancing agricultural foundation models

Computers and Electronics in Agriculture, Год журнала: 2025, Номер 231, С. 109908 - 109908

Опубликована: Янв. 22, 2025

Язык: Английский

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Key technologies in apple harvesting robot for standardized orchards: A comprehensive review of innovations, challenges, and future directions

Computers and Electronics in Agriculture, Год журнала: 2025, Номер 235, С. 110343 - 110343

Опубликована: Апрель 3, 2025

Язык: Английский

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Simplified Deep Learning for Accessible Fruit Quality Assessment in Small Agricultural Operations

Applied Sciences, Год журнала: 2024, Номер 14(18), С. 8243 - 8243

Опубликована: Сен. 13, 2024

Fruit quality assessment is vital for ensuring consumer satisfaction and marketability in agriculture. This study explores deep learning techniques assessing fruit quality, focusing on practical deployment resource-constrained environments. Two approaches were compared: training a convolutional neural network (CNN) from scratch fine-tuning pre-trained MobileNetV2 model through transfer learning. The performance of these models was evaluated using subset the Fruits-360 dataset chosen to simulate real-world conditions small-scale producers. selected its compact size efficiency, suitable devices with limited computational resources. Both achieved high accuracy, demonstrating faster convergence slightly better performance. Feature map visualizations provided insight into model’s decision-making, highlighting damaged areas fruits which enhances transparency trust end users. underscores potential modernize assessment, offering practical, efficient, interpretable tools farmers.

Язык: Английский

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An apple fruit localization system based on accurate and flexible hand-eye pose acquisition for robotic harvesting

Computers and Electronics in Agriculture, Год журнала: 2024, Номер 229, С. 109705 - 109705

Опубликована: Дек. 4, 2024

Язык: Английский

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