Flower Species Detection System Using Deep Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Flower Species Detection System Using Deep Convolutional Neural Networks

Published:2022 Issue: Volume: Page:217-231
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
Short-container-title:

Author:

Solanki Arun,Singh Tarana

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-0284-0_17

Reference37 articles.

1. Singh SP, Solanki A, Singh T, Tayal A (2021) Internet of intelligent things: injection of intelligence into IoT devices. In: Artificial intelligence to solve pervasive internet of things issues. Academic Press, pp 85–102

2. Issa MB, Daraghmeh M, Jararweh Y, Al-Ayyoub M, Alsmirat M, Benkhelifa E (2017) Using logistic regression to improve virtual machines management in cloud computing systems. In: 2017 IEEE 14th international conference on Mobile Ad Hoc and Sensor Systems (MASS), 22–25 Oct. 2017

3. Zeiler MD, Fergus R (2014) Visualizing and understanding convolutional networks. In: Fleet DJ, Pajdla T, Schiele B, Tuytelaars T (eds) ECCV, volume 8689 of Lecture Notes in Computer Science. Spring, pp 818–833

4. Redmon J, Divvala S, Girshick R et al (2016) You only look once: unified, real-time object detection. In: Proceeding IEEE conference computer vision and pattern recognition, Las Vegas, NV, June 2016, pp 779–788

5. Singh T, Nayyar A, Solanki A (2020) Multilingual opinion mining movie recommendation system using RNN. In: Proceedings of first international conference on computing, communications, and cyber-security (IC4S 2019). Springer, Singapore, pp 589–605

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3. Using Deep Neural Nets for Flower Classification;2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT);2023-07-06

4. Flower Classification Utilisizing Tensor Processing Unit Mechanism;2023 2nd International Conference for Innovation in Technology (INOCON);2023-03-03

5. Grey Wolf Optimization-Based CNN-LSTM Network for the Prediction of Energy Consumption in Smart Home Environment;IEEE Access;2023

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