Image based fruit category classification by 13-layer deep convolutional neural network and data augmentation
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Summary
This study designed and validated a 13-layer convolutional neural network (CNN) that is effective in image-based fruit classification and observed using data augmentation can increase the overall accuracy.
- Type
- article
- Published
- 2019-02-01
- Cited by
- 352
- References
- 48
- OpenAlex
- https://openalex.org/W2758007480
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:13386452
Keywords
Computer science, Pooling, Convolutional neural network, Artificial intelligence, Stochastic gradient descent
References
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- Classification of Fruits Using Computer Vision and a Multiclass Support Vector Machine
- Visual Tracking Using Max-Average Pooling and Weight-Selection Strategy
- Content-based image quality metric using similarity measure of moment vectors
- A study of the effect of noise injection on the training of artificial neural networks
- Identification of Progressive Mild Cognitive Impairment Patients Using Incomplete Longitudinal MRI Scans
- Underwater 3D Surface Measurement Using Fringe Projection Based Scanning Devices
- Electronic nose based on partition column integrated with gas sensor for fruit identification and classification
- Classification of E-Nose Aroma Data of Four Fruit Types by ABC-Based Neural Network
- iDoctor: Personalized and professionalized medical recommendations based on hybrid matrix factorization
- Fruit classification by biogeography‐based optimization and feedforward neural network
- Effect of Melatonin in Epithelial Mesenchymal Transition Markers and Invasive Properties of Breast Cancer Stem Cells of Canine and Human Cell Lines
- Deep unfolding inference for supervised topic model
- Brain early infarct detection using gamma correction extreme-level eliminating with weighting distribution.
- An adaptive over-split and merge algorithm for page segmentation
- GroRec: A Group-Centric Intelligent Recommender System Integrating Social, Mobile and Big Data Technologies
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- Breast cancer detection via Hu moment invariant and feedforward neural network
- Abnormal breast identification by nine-layer convolutional neural network with parametric rectified linear unit and rank-based stochastic pooling
- An effective model based on Haar wavelet entropy and genetic algorithm for fruit identification
- Spoken keyword search system using improved ASR engine and novel template-based keyword scoring
- STUDY ON A NEW REMOTE SENSING IMAGE CLASSIFICATION METHOD AND ITS APPLICATION
- ABCD rule and pre-trained CNNs for melanoma diagnosis
- Gingivitis Identification via Grey-level Cooccurrence Matrix and Extreme Learning Machine
- Fruit category classification via an eight-layer convolutional neural network with parametric rectified linear unit and dropout technique
- A comprehensive review of fruit and vegetable classification techniques
- Palm Oil Fresh Fruit Bunch Ripeness Grading Recognition Using Convolutional Neural Network
- An effective analysis of deep learning based approaches for audio based feature extraction and its visualization
- An Improvised Algorithm For Computer Vision Based Cashew Grading System Using Deep CNN
- Using Deep Convolutional Neural Network for oak acorn viability recognition based on color images of their sections
- Multi-grade brain tumor classification using deep CNN with extensive data augmentation
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