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Vegetables

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Detection of Green Asparagus Using Improved Mask R-CNN for Automatic Harvesting.

Sensors (Basel, Switzerland)
Advancements in deep learning and computer vision have led to the discovery of numerous effective solutions to challenging problems in the field of agricultural automation. With the aim to improve the detection precision in the autonomous harvesting ...

Fruit Sizing in Orchard: A Review from Caliper to Machine Vision with Deep Learning.

Sensors (Basel, Switzerland)
Forward estimates of harvest load require information on fruit size as well as number. The task of sizing fruit and vegetables has been automated in the packhouse, progressing from mechanical methods to machine vision over the last three decades. Thi...

Automatic Chinese Food recognition based on a stacking fusion model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
With commercialization of deep learning models, daily precision dietary record based on images from smartphones becomes possible. This study took advantage of Deep-learning techniques on visual recognition tasks and proposed a big-data-driven Deep-le...

Large-scale automatic extraction of agricultural greenhouses based on high-resolution remote sensing and deep learning technologies.

Environmental science and pollution research international
Widely used agricultural greenhouses are critical in the development of facility agriculture because of not only their huge capacity in food and vegetable supplies, but also their environmental and climatic effects. Therefore, it is important to obta...

Rapid detection of residual chlorpyrifos and pyrimethanil on fruit surface by surface-enhanced Raman spectroscopy integrated with deep learning approach.

Scientific reports
Chlorpyrifos and pyrimethanil are widely used insecticides/fungicides in agriculture. The residual pesticides/fungicides remaining in fruits and vegetables may do harm to human health if they are taken without notice by the customers. Therefore, it i...

Optical sensing for real-time detection of food-borne pathogens in fresh produce using machine learning.

Science progress
Contaminated fresh produce remains a prominent catalyst for food-borne illnesses, prompting the need for swift and precise pathogen detection to mitigate health risks. This paper introduces an innovative strategy for identifying food-borne pathogens ...

Deep learning-based prediction of plant height and crown area of vegetable crops using LiDAR point cloud.

Scientific reports
Remote sensing has been increasingly used in precision agriculture. Buoyed by the developments in the miniaturization of sensors and platforms, contemporary remote sensing offers data at resolutions finer enough to respond to within-farm variations. ...

Surface-Enhanced Raman Scattering Imaging Assisted by Machine Learning Analysis: Unveiling Pesticide Molecule Permeation in Crop Tissues.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Surface-enhanced Raman scattering (SERS) imaging technology faces significant technical bottlenecks in ensuring balanced spatial resolution, preventing image bias induced by substrate heterogeneity, accurate quantitative analysis, and substrate prepa...

Machine learning trained poly (3,4-ethylenedioxythiophene) functionalized carbon matrix suspended Cu nanoparticles for precise monitoring of nitrite from pickled vegetables.

Food chemistry
Precise monitoring of nitrite from real samples has gained significant attention due to its detrimental impact on human health. Herein, we have fabricated poly(3,4-ethylenedioxythiophene) functionalized carbon matrix suspended Cu nanoparticles (PEDOT...

Identifying heavy metal sources and health risks in soil-vegetable systems of fragmented vegetable fields based on machine learning, positive matrix factorization model and Monte Carlo simulation.

Journal of hazardous materials
Urban fragmented vegetable fields offer fresh produce but pose a potential risk of heavy metal (HM) exposure. Thus, this study investigated HM sources and health risks in the soil-vegetable systems of Chongqing's central urban area. Results indicated...