A Study on CNN Based Transfer Learning for Recognition of Flower Species

Author:

BOZKURT Ferhat

Publisher

European Journal of Science and Technology

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference32 articles.

1. Arinda, Y. K., Rahman, M. A., & Alamsyah, D. (2018). Klasifikasi Jenis Bunga menggunakan SVM dengan Fitur HSV dan HOG. Ijccs, no. x, 1-12.

2. Bayram, E., & Nabiyev, V. (2021). Classification of Camouflage Images Using Local Binary Patterns (LBP). In 2021 29th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). IEEE.

3. Christenhusz, M. J., & Byng, J. W. (2016). The number of known plants species in the world and its annual increase. Phytotaxa, 261(3), 201-217.

4. Chen, B., Liu, J., Sun, J., Liu, J. (2019). Flowers Classification via Deep Learning Models. http://noiselab.ucsd.edu/ECE228_2019/Reports/Report40.pdf (accessed November 10, 2021).

5. Coban, O. (2021). IRText: An Item Response Theory-Based Approach for Text Categorization. Arabian Journal for Science and Engineering, 1-17.

Cited by 6 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. Combining Image Classification and Unmanned Aerial Vehicles to Estimate the State of Explorer Roses;AgriEngineering;2024-04-16

2. Transfer Derin Öğrenme Teknikleri ile Görüntü Sınıflandırmada Aktivasyon Fonksiyonlarının Performans Üzerindeki Etkisi;Afyon Kocatepe University Journal of Sciences and Engineering;2024-04-14

3. A Comprehensive Method for Flower Detection by DL: A Comparative Study between Multiple Statistical Models;2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT);2024-02-09

4. Early-stage heart failure disease prediction with deep learning approach;Journal of Scientific Reports-A;2023-12-31

5. Classification of Mixed Color Rose Types Using Convolutional Neural Network;2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI);2023-12-09

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3