一个计算机视觉系统和机器学习算法用于预测物理化学变化和涂层甜桃的分类
Yashar Shahedi1, Mohsen Zandi1, Mandana Bimakr1
1Department of Food Science and Engineering, Faculty of Agriculture, University of Zanjan, Zanjan, 45371-38791, Iran.
Heliyon
|November 5, 2024
概括
人工神经网络 (ANN) 和自适应神经模糊推理系统 (ANFIS) 模型使用图像分析准确预测甜桃的质量. 这些模型在分类缺陷和预测储存期间的物理和化学性质方面达到90%以上的准确性.
科学领域:
- 农业科学 农业科学
- 计算机科学 计算机科学
- 食品科学 食品科学 食品科学
背景情况:
- 在储存期间监测甜桃的质量对于减少收获后损失至关重要.
- 评估水果质量的传统方法往往耗时且主观.
- 有效的质量评估需要客观,非破坏性的方法.
研究的目的:
- 通过使用视觉和定性特征,调查储存期间甜桃表面缺陷的变化.
- 用图像分析和计算模型预测甜桃的物理和化学特性.
- 在储存期间准确地分类甜桃的质量等级.
主要方法:
- 使用的人工神经网络 (ANN) 和自适应神经模糊推理系统 (ANFIS) 模型.
- 雇佣了多层感知器 (MLP),用于ANN的特定功能,以及Mamdani系统,用于ANFIS的各种会员功能.
- 从RGB图像中结合色彩统计和纹理特征与物理化学性质 (体重减轻,度,酸度,酸素含量) 进行模型训练和预测.
主要成果:
- 通过图像颜色和纹理特征,ANN和ANFIS模型都准确地预测了甜桃的物理和化学特性.
- 通过四种不同的算法,ANN和ANFIS模型在分类甜桃质量等级方面取得了超过90%的准确性.
- 这些模型在预测体重减轻,坚硬度,可定位的酸度和总酸含量方面表现出很高的准确性.
结论:
- ANN和ANFIS模型是用于甜桃的非破坏性,定性分类的有效工具.
- 开发的模型提供了令人满意的性能来预测储存期间的关键物理和化学性质.
- 基于图像的分析与智能系统相结合,为自动化水果质量评估提供了一个有希望的方法.
更多相关视频
07:25Combining Histochemical Staining and Image Analysis to Quantify Starch in the Ovary Primordia of Sweet Cherry during Winter Dormancy
Published on: March 20, 2019
6.2K
08:02Author Spotlight: Innovative Ice Cream Melting Behavior Analysis Through a Computer Vision System
Published on: October 4, 2024
2.3K
相关概念视频
01:01Classification of Titrimetric Analysis Based on Reaction Types
Titrimetric analysis in solution chemistry involves measuring the volume of solutions and is often called volumetric analysis. The standard solution of known concentration in the burette is called the titrant, whereas the solution of unknown concentration in the flask is called the analyte, or titrand. Titrimetric analyses can be classified into four types based on the reactions between the titrant and analyte.
Titrations between an acid and a base lead to neutralization reactions that form...
Titrations between an acid and a base lead to neutralization reactions that form...
01:28Classification and Mechanical Properties of Synthetic Polymers
Synthetic polymers are classified as elastomers, fibers, or plastics based on their crystallinity. Crystallinity, the degree of long-range order in the solid state, influences the mechanical properties (stretching or contracting) of elastomers. Elastomers are flexible polymers that can expand or contract easily upon the application of an external force. They have numerous crosslinks that pull them back into their original shape when stress is removed. Silicones, for instance, are highly elastic...
01:26Classification of Systems-I
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
01:31Classification of Systems-II
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,