相关论文: Leaf Angle Estimation using Mask R-CNN and LETR Vi…

This paper presents a framework which uses computer vision algorithms to standardise images and analyse them for identifying crop diseases automatically. The tools are created to bridge the information gap between farmers, advisory call…

High efficiency in precision farming depends on accurate tools to perform weed detection and mapping of crops. This allows for precise removal of harmful weeds with a lower amount of pesticides, as well as increase of the harvest's yield by…

High-throughput plant phenotyping, the quantitative measurement of observable plant traits, is critical for modern breeding but remains constrained by a "phenotyping bottleneck," where manual data collection is labor-intensive and prone to…

Plant phenotyping is a central task in agriculture, as it describes plants' growth stage, development, and other relevant quantities. Robots can help automate this process by accurately estimating plant traits such as the number of leaves,…

Identification, classification, and quantification of crop defects are of paramount of interest to the farmers for preventive measures and decrease the yield loss through necessary remedial actions. Due to the vast agricultural field,…

Robotic apple harvesting has received much research attention in the past few years due to growing shortage and rising cost in labor. One key enabling technology towards automated harvesting is accurate and robust apple detection, which…

Foundation models and vision-language pre-training have significantly advanced Vision-Language Models (VLMs), enabling multimodal processing of visual and linguistic data. However, their application in domain-specific agricultural tasks,…

License plate scanners have grown in popularity in parking lots during the past few years. In order to quickly identify license plates, traditional plate recognition devices used in parking lots employ a fixed source of light and shooting…

Accurate estimation of total leaf area (TLA) is crucial for evaluating plant growth, photosynthetic activity, and transpiration. However, it remains challenging for bushy plants like dwarf tomatoes due to their complex canopies. Traditional…

This study, our main topic is to devlop a new deep-learning approachs for plant leaf disease identification and detection using leaf image datasets. We also discussed the challenges facing current methods of leaf disease detection and how…

Labor shortages in fruit crop production have prompted the development of mechanized and automated machines as alternatives to labor-intensive orchard operations such as harvesting, pruning, and thinning. Agricultural robots capable of…

Most of the traditional convolutional neural networks (CNNs) implements bottom-up approach (feed-forward) for image classifications. However, many scientific studies demonstrate that visual perception in primates rely on both bottom-up and…

The complex background in the soil image collected in the field natural environment will affect the subsequent soil image recognition based on machine vision. Segmenting the soil center area from the soil image can eliminate the influence…

Plant water stress may occur due to the limited availability of water to the roots/soil or due to increased transpiration. These factors adversely affect plant physiology and photosynthetic ability to the extent that it has been shown to…

Land Cover (LC) image classification has become increasingly significant in understanding environmental changes, urban planning, and disaster management. However, traditional LC methods are often labor-intensive and prone to human error.…

Plant root research can provide a way to attain stress-tolerant crops that produce greater yield in a diverse array of conditions. Phenotyping roots in soil is often challenging due to the roots being difficult to access and the use of time…

In the Agriculture sector, control of plant leaf diseases is crucial as it influences the quality and production of plant species with an impact on the economy of any country. Therefore, automated identification and classification of plant…

Early detection of cancer can help improve patient prognosis by early intervention. Head and neck cancer is diagnosed in specialist centres after a surgical biopsy, however, there is a potential for these to be missed leading to delayed…

Reliable large-scale data on the state of forests is crucial for monitoring ecosystem health, carbon stock, and the impact of climate change. Current knowledge of tree species distribution relies heavily on manual data collection in the…

Increasing deployment of photovoltaics (PV) plants demands for cheap and fast inspection. A viable tool for this task is thermographic imaging by unmanned aerial vehicles (UAV). In this work, we develop a computer vision tool for the…