AIMC Topic: Fruit

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The Novel Combination of Nano Vector Network Analyzer and Machine Learning for Fruit Identification and Ripeness Grading.

Sensors (Basel, Switzerland)
Fruit classification is required in many smart-farming and industrial applications. In the supermarket, a fruit classification system may be used to help cashiers and customer to identify the fruit species, origin, ripeness, and prices. Some methods,...

A novel knowledge extraction method based on deep learning in fruit domain.

Scientific reports
Knowledge extraction aims to identify entities and extract relations between them from unstructured text, which are in the form of triplets. Analysis of the fruit nutrition domain corpus revealed many overlapping triplets, that is, multiple correspon...

Automatic Classification Service System for Citrus Pest Recognition Based on Deep Learning.

Sensors (Basel, Switzerland)
Plant diseases are a major cause of reduction in agricultural output, which leads to severe economic losses and unstable food supply. The citrus plant is an economically important fruit crop grown and produced worldwide. However, citrus plants are ea...

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...

Determining the Stir-Frying Degree of Praeparatus Based on Deep Learning and Transfer Learning.

Sensors (Basel, Switzerland)
Gardeniae Fructus (GF) is one of the most widely used traditional Chinese medicines (TCMs). Its processed product, Praeparatus (GFP), is often used as medicine; hence, there is an urgent need to determine the stir-frying degree of GFP. In this paper...

Factors affecting energy efficiency of microwave drying of foods: an updated understanding.

Critical reviews in food science and nutrition
Microwave drying (MWD) is an efficient dielectric drying method in food, with advantages such as volumetric heating, fast drying, safety, and good product quality. As a key indicator of a dryer's market value, energy efficiency is of concern to selle...

Real-Time Prediction of Growth Characteristics for Individual Fruits Using Deep Learning.

Sensors (Basel, Switzerland)
Understanding the growth status of fruits can enable precise growth management and improve the product quality. Previous studies have rarely used deep learning to observe changes over time, and manual annotation is required to detect hidden regions o...

Intelligent yield estimation for tomato crop using SegNet with VGG19 architecture.

Scientific reports
Yield estimation (YE) of the crop is one of the main tasks in fruit management and marketing. Based on the results of YE, the farmers can make a better decision on the harvesting period, prevention strategies for crop disease, subsequent follow-up fo...

Learning-Based Slip Detection for Robotic Fruit Grasping and Manipulation under Leaf Interference.

Sensors (Basel, Switzerland)
Robotic harvesting research has seen significant achievements in the past decade, with breakthroughs being made in machine vision, robot manipulation, autonomous navigation and mapping. However, the missing capability of obstacle handling during the ...

A survey on computational spectral reconstruction methods from RGB to hyperspectral imaging.

Scientific reports
Hyperspectral imaging enables many versatile applications for its competence in capturing abundant spatial and spectral information, which is crucial for identifying substances. However, the devices for acquiring hyperspectral images are typically ex...