Flowering Index Intelligent Detection of Spray Rose Cut Flowers Using an Improved YOLOv5s Model
Addressing the current reliance on manual sorting and grading of spray rose cut flowers, this paper proposed an improved YOLOv5s model for intelligent recognition and grading detection of rose color series and flowering index of spray rose cut flowers. By incorporating small-scale anchor boxes and s...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-10-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/14/21/9879 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846173572004839424 |
|---|---|
| author | Junyan Li Ming Li |
| author_facet | Junyan Li Ming Li |
| author_sort | Junyan Li |
| collection | DOAJ |
| description | Addressing the current reliance on manual sorting and grading of spray rose cut flowers, this paper proposed an improved YOLOv5s model for intelligent recognition and grading detection of rose color series and flowering index of spray rose cut flowers. By incorporating small-scale anchor boxes and small object feature output, the model enhanced the annotation accuracy and the detection precision for occluded rose flowers. Additionally, a convolutional block attention module attention mechanism was integrated into the original network structure to improve the model’s feature extraction capability. The WIoU loss function was employed in place of the original CIoU loss function to increase the precision of the model’s post-detection processing. Test results indicated that for two types of spray rose cut flowers, Orange Bubbles and Yellow Bubbles, the improved YOLOv5s model achieved an accuracy and recall improvement of 10.2% and 20.0%, respectively. For randomly collected images of spray rose bouquets, the model maintained a detection accuracy of 95% at a confidence threshold of 0.8. |
| format | Article |
| id | doaj-art-05bb65c7abc649bbb164b14c53878036 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-05bb65c7abc649bbb164b14c538780362024-11-08T14:33:40ZengMDPI AGApplied Sciences2076-34172024-10-011421987910.3390/app14219879Flowering Index Intelligent Detection of Spray Rose Cut Flowers Using an Improved YOLOv5s ModelJunyan Li0Ming Li1College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210095, ChinaSchool of Electrical Engineering, Anhui Polytechnic University, Wuhu 214000, ChinaAddressing the current reliance on manual sorting and grading of spray rose cut flowers, this paper proposed an improved YOLOv5s model for intelligent recognition and grading detection of rose color series and flowering index of spray rose cut flowers. By incorporating small-scale anchor boxes and small object feature output, the model enhanced the annotation accuracy and the detection precision for occluded rose flowers. Additionally, a convolutional block attention module attention mechanism was integrated into the original network structure to improve the model’s feature extraction capability. The WIoU loss function was employed in place of the original CIoU loss function to increase the precision of the model’s post-detection processing. Test results indicated that for two types of spray rose cut flowers, Orange Bubbles and Yellow Bubbles, the improved YOLOv5s model achieved an accuracy and recall improvement of 10.2% and 20.0%, respectively. For randomly collected images of spray rose bouquets, the model maintained a detection accuracy of 95% at a confidence threshold of 0.8.https://www.mdpi.com/2076-3417/14/21/9879spray roseYOLOv5flowering indexcut flowerdetection |
| spellingShingle | Junyan Li Ming Li Flowering Index Intelligent Detection of Spray Rose Cut Flowers Using an Improved YOLOv5s Model Applied Sciences spray rose YOLOv5 flowering index cut flower detection |
| title | Flowering Index Intelligent Detection of Spray Rose Cut Flowers Using an Improved YOLOv5s Model |
| title_full | Flowering Index Intelligent Detection of Spray Rose Cut Flowers Using an Improved YOLOv5s Model |
| title_fullStr | Flowering Index Intelligent Detection of Spray Rose Cut Flowers Using an Improved YOLOv5s Model |
| title_full_unstemmed | Flowering Index Intelligent Detection of Spray Rose Cut Flowers Using an Improved YOLOv5s Model |
| title_short | Flowering Index Intelligent Detection of Spray Rose Cut Flowers Using an Improved YOLOv5s Model |
| title_sort | flowering index intelligent detection of spray rose cut flowers using an improved yolov5s model |
| topic | spray rose YOLOv5 flowering index cut flower detection |
| url | https://www.mdpi.com/2076-3417/14/21/9879 |
| work_keys_str_mv | AT junyanli floweringindexintelligentdetectionofsprayrosecutflowersusinganimprovedyolov5smodel AT mingli floweringindexintelligentdetectionofsprayrosecutflowersusinganimprovedyolov5smodel |