Plant image recognition with deep learning: A review
Y Chen, Y Huang, Z Zhang, Z Wang, B Liu, C Liu… - … and Electronics in …, 2023 - Elsevier
Significant advances in the field of digital image processing have been achieved in recent
years using deep learning, which has significantly exceeded previous methods. Deep …
years using deep learning, which has significantly exceeded previous methods. Deep …
Applications of computer vision and machine learning techniques for digitized herbarium specimens: A systematic literature review
Herbaria contain the treasure of millions of specimens that have been preserved for several
years for scientific studies. To increase the rate of scientific discoveries, digitization of these …
years for scientific studies. To increase the rate of scientific discoveries, digitization of these …
A novel approach for apple leaf disease image segmentation in complex scenes based on two-stage DeepLabv3+ with adaptive loss
S Zhu, W Ma, J Lu, B Ren, C Wang, J Wang - Computers and Electronics in …, 2023 - Elsevier
In complex environments, overlapping leaves and uneven light can make pixels of leaf
edges difficult to identify, resulting in a poor segmentation performance of the target leaf. In …
edges difficult to identify, resulting in a poor segmentation performance of the target leaf. In …
Spatial-temporal mapping of forest vegetation cover changes along highways in Brunei using deep learning techniques and Sentinel-2 images
Infrastructure development is a leading driver of forest cover loss in the tropics, resulting in a
significant decrease in biodiversity. With recent advancements in digital image processing …
significant decrease in biodiversity. With recent advancements in digital image processing …
From leaves to labels: Building modular machine learning networks for rapid herbarium specimen analysis with LeafMachine2
Premise Quantitative plant traits play a crucial role in biological research. However,
traditional methods for measuring plant morphology are time consuming and have limited …
traditional methods for measuring plant morphology are time consuming and have limited …
Monitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies
Tropical leaf phenology—particularly its variability at the tree-crown scale—dominates the
seasonality of carbon and water fluxes. However, given enormous species diversity …
seasonality of carbon and water fluxes. However, given enormous species diversity …
[HTML][HTML] An image dataset of cleared, x-rayed, and fossil leaves vetted to plant family for human and machine learning
Abstract Leaves are the most abundant and visible plant organ, both in the modern world
and the fossil record. Identifying foliage to the correct plant family based on leaf architecture …
and the fossil record. Identifying foliage to the correct plant family based on leaf architecture …
[Retracted] Deep Learning‐Based Leaf Region Segmentation Using High‐Resolution Super HAD CCD and ISOCELL GW1 Sensors
Super HAD CCD and ISOCELL GW1 imaging sensors are used for capturing images in high‐
resolution cameras nowadays. These high‐resolution camera sensors were used in this …
resolution cameras nowadays. These high‐resolution camera sensors were used in this …
[HTML][HTML] Research of segmentation recognition of small disease spots on apple leaves based on hybrid loss function and cbam
X Zhang, D Li, X Liu, T Sun, X Lin, Z Ren - Frontiers in Plant Science, 2023 - frontiersin.org
Identification technology of apple diseases is of great significance in improving production
efficiency and quality. This paper has used apple Alternaria blotch and brown spot disease …
efficiency and quality. This paper has used apple Alternaria blotch and brown spot disease …
A deep learning-based approach for detecting plant organs from digitized herbarium specimen images
Herbarium specimens are excellent sources of botanical information to facilitate
understanding and monitoring the evolution of plants and their effects on global climate …
understanding and monitoring the evolution of plants and their effects on global climate …