Nov 7, 2022 · We designed and developed a strawberry growth detection algorithm, SDNet (Strawberry Detect Net). The algorithm is based on the YOLOX model.

Dec 1, 2022 · The algorithm is based on the YOLOX model and replaces the original CSP block in the backbone network with a self-designed feature extraction ...

MS-YOLOv5: a lightweight algorithm for strawberry ripeness detection based on deep learning · Computer Science, Agricultural and Food Sciences. Systems Science ...

In this paper, a fast detection method of strawberry ripeness and picking point based on improved YOLO V8-Pose (You Only Look Once) and RGB-D depth camera is ...

Cuong et al. [26] utilized technology based on the YOLOv4 model for real-time monitoring on mobile devices, achieving a recognition accuracy of 98.26% on the ...

In this paper, a fast detection method of strawberry ripeness and picking point based on improved YOLO V8-Pose (You Only Look Once) and RGB-D depth camera is ...

Dec 1, 2024 · This paper presents SGSNet, a lightweight deep learning model designed for the fast and accurate detection of various strawberry growth stages.

In this paper, we propose DSE-YOLO (Detail-Semantics Enhancement You Only Look Once) to detect multi-stage strawberries.

Aug 11, 2024 · This study evaluates the performance of YOLOv8 model configurations for instance segmentation of strawberries into ripe and unripe stages in an open field ...

The technique employs a deep learning based object detection model to count the number of flowers and fruits of the strawberry canopy. We used a smartphone to ...