ArticleScientific reports2021
Apple quality identification and classification by image processing based on convolutional neural networks.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Deep learning-based seed germination prediction using morphological traits and RGB images.BMC plant biology · 2026Article
- Designing of guava quality classification model based on ANOVA and machine learning.Scientific reports · 2025Article
- Revolutionizing agriculture: A comprehensive review on artificial intelligence applications in enhancing properties of agricultural produce.Food chemistry: X · 2025Review
- A Comprehensive Review of Deep Learning in Computer Vision for Monitoring Apple Tree Growth and Fruit Production.Sensors (Basel, Switzerland) · 2025Review
- A dataset of annotated African plum images from Cameroon for AI-based quality assessment.Data in brief · 2025Article
- Automated measurement of ascorbic acid levels in camu-camu using Vision Transformer.Frontiers in plant science · 2025Article
- Article
- Apple varieties, diseases, and distinguishing between fresh and rotten through deep learning approaches.PloS one · 2025Article
- Egg mass classification considering the hatching process of Pomacea canaliculata.Scientific reports · 2024Article
- Fusing global context with multiscale context for enhanced breast cancer classification.Scientific reports · 2024Article
- Rating pome fruit quality traits using deep learning and image processing.Plant direct · 2024Article
- Enhancing Jujube Forest Growth Estimation and Disease Detection Using a Novel Diffusion-Transformer Architecture.Plants (Basel, Switzerland) · 2024Article
- Unique Plant Resources and Distribution Patterns in the Valley Forest of the Irtysh River Basin.Plants (Basel, Switzerland) · 2024Article
- Quality detection and grading of peach fruit based on image processing method and neural networks in agricultural industry.Frontiers in plant science · 2024Article
- Quasi Real-Time Apple Defect Segmentation Using Deep Learning.Sensors (Basel, Switzerland) · 2023Article
- Analyzing the Quality Parameters of Apples by Spectroscopy from Vis/NIR to NIR Region: A Comprehensive Review.Foods (Basel, Switzerland) · 2023Review
- Deep Learning-Based Intelligent Apple Variety Classification System and Model Interpretability Analysis.Foods (Basel, Switzerland) · 2023Article
- Real-Time Grading of Defect Apples Using Semantic Segmentation Combination with a Pruned YOLO V4 Network.Foods (Basel, Switzerland) · 2022Article
- Circle Fitting Based Image Segmentation and Multi-Scale Block Local Binary Pattern Based Distinction of Ring Rot and Anthracnose on Apple Fruits.Frontiers in plant science · 2022Article
- Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This work researched apple quality identification and classification from real images containing complicated disturbance information (background was similar to the surface of the apples). This paper proposed a novel model based on convolutional neural networks (CNN) which aimed at accurate and fast grading of apple quality. Specific, complex, and useful image characteristics for detection and classification were captured by the proposed model. Compared with existing methods, the proposed model could better learn high-order features of two adjacent layers that were not in the same channel but were very related. The proposed model was trained and validated, with best training and validation accuracy of 99% and 98.98% at 2590th and 3000th step, respectively. The overall accuracy of the proposed model tested using an independent 300 apple dataset was 95.33%. The results showed that the training accuracy, overall test accuracy and training time of the proposed model were better than Google Inception v3 model and traditional imaging process method based on histogram of oriented gradient (HOG), gray level co-occurrence matrix (GLCM) features merging and support vector machine (SVM) classifier. The proposed model has great potential in Apple's quality detection and classification.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.