Related Concept Videos
02:16Light Acquisition
8.4K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.4K
01:24Vision
52.9K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
52.9K
02:35Key Elements for Plant Nutrition
18.6K
Like all living organisms, plants require organic and inorganic nutrients to survive, reproduce, grow and maintain homeostasis. To identify nutrients that are essential for plant functioning, researchers have leveraged a technique called hydroponics. In hydroponic culture systems, plants are grown—without soil—in water-based solutions containing nutrients. At least 17 nutrients have been identified as essential elements required by plants. Plants acquire these elements from the...
18.6K
You might also read
Related Articles
Articles linked to this work by shared authors, journal, and citation graph.
Sort by
Same author
Distance Error Correction in Time-of-Flight Cameras Using Asynchronous Integration Time.
Sensors (Basel, Switzerland)·2020
Related Experiment Video
Updated: Jun 3, 2025
08:47
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
Published on: February 9, 2024
1.3K
Attention Score-Based Multi-Vision Transformer Technique for Plant Disease Classification.
1Department of AI & Big Data, Honam University, Gwangju 62399, Republic of Korea.
Sensors (Basel, Switzerland)
|January 11, 2025
Summary
This study introduces an advanced plant disease classification framework using the Multi-Vision Transformer (Multi-ViT) model. It achieves over 99% accuracy by analyzing multiple leaf images for precise disease diagnosis.
Area of Science:
- Agricultural Science
- Computer Science
- Plant Pathology
Background:
- Accurate plant disease diagnosis is crucial for crop yield and food security.
- Traditional methods often rely on single-leaf analysis, limiting diagnostic accuracy.
- The Vision Transformer (ViT) architecture shows promise for image-based classification tasks.
Purpose of the Study:
- To develop an advanced plant disease classification framework using a novel attention-based Multi-Vision Transformer (Multi-ViT) model.
- To improve diagnostic accuracy by analyzing multiple leaf images for a holistic symptom assessment.
- To overcome the limitations of single-leaf-based diagnoses in plant pathology.
Main Methods:
- Developed an Attention Score-Based Multi-Vision Transformer (Multi-ViT) model.
- Integrated a novel attention mechanism to prioritize relevant features from multiple leaf images.
- Aggregated diverse feature representations by combining outputs from multiple ViTs.
Main Results:
- Achieved over 99% accuracy in plant disease classification across apple, grape, and tomato datasets.
- Significantly improved F1 scores compared to traditional methods like ResNet, VGG, and MobileNet.
- Demonstrated the model's capability for precise and reliable diagnosis of plant diseases.
Conclusions:
- The proposed Multi-ViT framework offers a superior approach for plant disease classification.
- Analyzing multiple leaf images with advanced AI models enhances diagnostic precision.
- This framework holds significant potential for agricultural applications and disease management.