Please wait, while we are loading the content...
Please wait, while we are loading the content...
| Content Provider | frontiers |
|---|---|
| Author | Wang, Dandan He, Dongjian |
| Abstract | The accurate detection and segmentation of apples during growth stage is essential for yield estimation, timely harvesting, and retrieving growth information. However, factors such as the uncertain illumination, overlaps and occlusions of apples, homochromatic background and the gradual change in the ground color of apples from green to red, bring great challenges to the detection and segmentation of apples. To solve these problems, this study proposed an improved Mask Scoring region-based convolutional neural network (Mask Scoring R-CNN), known as MS-ADS, for accurate apple detection and instance segmentation in a natural environment. First, the ResNeSt, a variant of ResNet, combined with a feature pyramid network was used as backbone network to improve the feature extraction ability. Second, high-level architectures including R-CNN head and mask head were modified to improve the utilization of high-level features. Convolutional layers were added to the original R-CNN head to improve the accuracy of bounding box detection (bbox_mAP), and the Dual Attention Network was added to the original mask head to improve the accuracy of instance segmentation (mask_mAP). The experimental results showed that the proposed MS-ADS model effectively detected and segmented apples under various conditions, such as apples occluded by branches, leaves and other apples, apples with different ground colors and shadows, and apples divided into parts by branches and petioles. The recall, precision, false detection rate, and F1 score were 97.4%, 96.5%, 3.5%, and 96.9%, respectively. A bbox_mAP and mask_mAP of 0.932 and 0.920, respectively, were achieved on the test set, and the average run-time was 0.27 s per image. The experimental results indicated that the MS-ADS method detected and segmented apples in the orchard robustly and accurately with real-time performance. This study lays a foundation for follow-up work, such as yield estimation, harvesting, and automatic and long-term acquisition of apple growth information. |
| ISSN | 1664462X |
| DOI | 10.3389/fpls.2022.1016470 |
| Volume Number | 13 |
| Journal | Frontiers in Plant Science |
| Language | English |
| Publisher Date | 2022-12-02 |
| Access Restriction | Open |
| Subject Keyword | Detection Segmentation Attention mechanism Fruit Deep learning Mask scoring R-CNN |
| Content Type | Text |
| Resource Type | Article |
| Subject | Plant Science |
National Digital Library of India (NDLI) is a virtual repository of learning resources which is not just a repository with search/browse facilities but provides a host of services for the learner community. It is sponsored and mentored by Ministry of Education, Government of India, through its National Mission on Education through Information and Communication Technology (NMEICT). Filtered and federated searching is employed to facilitate focused searching so that learners can find the right resource with least effort and in minimum time. NDLI provides user group-specific services such as Examination Preparatory for School and College students and job aspirants. Services for Researchers and general learners are also provided. NDLI is designed to hold content of any language and provides interface support for 10 most widely used Indian languages. It is built to provide support for all academic levels including researchers and life-long learners, all disciplines, all popular forms of access devices and differently-abled learners. It is designed to enable people to learn and prepare from best practices from all over the world and to facilitate researchers to perform inter-linked exploration from multiple sources. It is developed, operated and maintained from Indian Institute of Technology Kharagpur.
Learn more about this project from here.
NDLI is a conglomeration of freely available or institutionally contributed or donated or publisher managed contents. Almost all these contents are hosted and accessed from respective sources. The responsibility for authenticity, relevance, completeness, accuracy, reliability and suitability of these contents rests with the respective organization and NDLI has no responsibility or liability for these. Every effort is made to keep the NDLI portal up and running smoothly unless there are some unavoidable technical issues.
Ministry of Education, through its National Mission on Education through Information and Communication Technology (NMEICT), has sponsored and funded the National Digital Library of India (NDLI) project.
| Sl. | Authority | Responsibilities | Communication Details |
|---|---|---|---|
| 1 | Ministry of Education (GoI), Department of Higher Education |
Sanctioning Authority | https://www.education.gov.in/ict-initiatives |
| 2 | Indian Institute of Technology Kharagpur | Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project | https://www.iitkgp.ac.in |
| 3 | National Digital Library of India Office, Indian Institute of Technology Kharagpur | The administrative and infrastructural headquarters of the project | Dr. B. Sutradhar bsutra@ndl.gov.in |
| 4 | Project PI / Joint PI | Principal Investigator and Joint Principal Investigators of the project |
Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon |
| 5 | Website/Portal (Helpdesk) | Queries regarding NDLI and its services | support@ndl.gov.in |
| 6 | Contents and Copyright Issues | Queries related to content curation and copyright issues | content@ndl.gov.in |
| 7 | National Digital Library of India Club (NDLI Club) | Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach | clubsupport@ndl.gov.in |
| 8 | Digital Preservation Centre (DPC) | Assistance with digitizing and archiving copyright-free printed books | dpc@ndl.gov.in |
| 9 | IDR Setup or Support | Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops | idr@ndl.gov.in |
|
Loading...
|