Fruit category classification by fractional Fourier entropy with rotation angle vector grid and stacked sparse autoencoder-Reference-Cited by-同舟云学术

Fruit category classification by fractional Fourier entropy with rotation angle vector grid and stacked sparse autoencoder

Published:2021-04-08 Issue: Volume: Page:
ISSN:0266-4720
Container-title:Expert Systems
language:en
Short-container-title:Expert Systems

Author:

Zhang Yu‐Dong¹²^ORCID,Satapathy Suresh Chandra³,Wang Shui‐Hua²

Affiliation:

1. School of Informatics University of Leicester Leicester UK

2. School of Computer Science and Technology Henan Polytechnic University Jiaozuo PR China

3. School of Computer Engineering KIIT Deemed to University Bhubaneswar India

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.12701

Reference36 articles.

1. Aok S. (2018).Fruit classification based on six layer convolutional neural network. Paper presented at the 23rd international conference on digital signal processing (DSP) Shanghai China.

2. Potential of Near-Infrared (NIR) Spectroscopy and Hyperspectral Imaging for Quality and Safety Assessment of Fruits: an Overview

3. Diagnosis of heart diseases by a secure Internet of Health Things system based on Autoencoder Deep Neural Network

4. Computer vision based fruit recognition and classification system;Gurucharan K.;International Journal of Future Generation Communication and Networking,2020

5. Automatic Fruit Classification Using Deep Learning for Industrial Applications

Cited by 15 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fruit Type Classification using Stacked Bi-directional Long Short Term Memory;2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT);2023-10-20

2. Intelligent Resource Allocation Using an Artificial Ecosystem Optimizer with Deep Learning on UAV Networks;Drones;2023-10-03

3. A novel CNN gap layer for growth prediction of palm tree plantlings;PLOS ONE;2023-08-11

4. Convolutional Neural Networks of Whole Jujube Fruits Prediction Model Based on Multi-Spectral Imaging Method;Chinese Journal of Electronics;2023-05

5. Fruit Image Classification Model Based on MobileNetV2 with Deep Transfer Learning Technique;Sustainability;2023-01-19