AIMC Topic: Vegetables

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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...

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...

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 ...

Improved Classification Approach for Fruits and Vegetables Freshness Based on Deep Learning.

Sensors (Basel, Switzerland)
Classification of fruit and vegetable freshness plays an essential role in the food industry. Freshness is a fundamental measure of fruit and vegetable quality that directly affects the physical health and purchasing motivation of consumers. In addit...

Vegetable Size Measurement Based on Stereo Camera and Keypoints Detection.

Sensors (Basel, Switzerland)
This work focuses on the problem of non-contact measurement for vegetables in agricultural automation. The application of computer vision in assisted agricultural production significantly improves work efficiency due to the rapid development of infor...

A novel deep learning-based method for detection of weeds in vegetables.

Pest management science
BACKGROUND: Precision weed control in vegetable fields can substantially reduce the required weed control inputs. Rapid and accurate weed detection in vegetable fields is a challenging task due to the presence of a wide variety of weed species at var...

Application of classic and soft computing for modeling yield and environmental final impact in vegetable production (a case study: transplanting onion in Isfahan province, Iran).

Environmental science and pollution research international
This study aimed to develop a precision model between inputs and yield, and also between inputs (indirect emissions) and environmental final index (EFI) in onion farms through regression models (classic computing) and artificial intelligence models (...

Robust seed germination prediction using deep learning and RGB image data.

Scientific reports
Achieving seed germination quality standards poses a real challenge to seed companies as they are compelled to abide by strict certification rules, while having only partial seed separation solutions at their disposal. This discrepancy results with w...

Combining novel technologies with interdisciplinary basic research to enhance horticultural crops.

The Plant journal : for cell and molecular biology
Horticultural crops mainly include fruits, vegetables, ornamental trees and flowers, and tea trees (Melaleuca alternifolia). They produce a variety of nutrients for the daily human diet in addition to the nutrition provided by staple crops, and some ...

Spectroscopy and imaging technologies coupled with machine learning for the assessment of the microbiological spoilage associated to ready-to-eat leafy vegetables.

International journal of food microbiology
Based on both new and previously utilized experimental data, the present study provides a comparative assessment of sensors and machine learning approaches for evaluating the microbiological spoilage of ready-to-eat leafy vegetables (baby spinach and...