Navigation path extraction for greenhouse cucumber-picking robots using the prediction-point Hough transform

Classification and detection of insects from field images using deep learning for smart pest management: A systematic review

Applications of machine vision in agricultural robot navigation: A review

A review of UAV platforms, sensors, and applications for monitoring of sugarcane crops

The harvesting operation is a recurring task in the production of any crop, thus making it an excellent candidate for automation. In protected horticulture, one of the crops with high added value is tomatoes. However, its robotic harvesting is still far from maturity. That said, the development of an accurate fruit detection system is a crucial step towards achieving fully automated robotic harvesting. Deep Learning (DL) and detection frameworks like Single Shot MultiBox Detector (SSD) or You Only Look Once (YOLO) are more robust and accurate alternatives with better response to highly complex scenarios. The use of DL can be easily used to detect tomatoes, but when their classification is intended, the task becomes harsh, demanding a huge amount of data. Therefore, this paper proposes the use of DL models (SSD MobileNet v2 and YOLOv4) to efficiently detect the tomatoes and compare those systems with a proposed histogram-based HSV colour space model to classify each tomato and determine its ripening stage, through two image datasets acquired. Regarding detection, both models obtained promising results, with the YOLOv4 model standing out with an F1-Score of 85.81%. For classification task the YOLOv4 was again the best model with an Macro F1-Score of 74.16%. The HSV colour space model outperformed the SSD MobileNet v2 model, obtaining results similar to the YOLOv4 model, with a Balanced Accuracy of 68.10%.

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Jiahua Wu

Papers

Navigation path extraction for greenhouse cucumber-picking robots using the prediction-point Hough transform

Extracting the navigation path of a tomato-cucumber greenhouse robot based on a median point Hough transform

An improved Yolov3 based on dual path network for cherry tomatoes detection

Detecting ripe fruits under natural occlusion and illumination conditions

Sugarcane nodes identification algorithm based on sum of local pixel of minimum points of vertical projection function