A CNN-Based Approach for Facial Emotion Detection-Reference-Cited by-同舟云学术

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A CNN-Based Approach for Facial Emotion Detection

Published:2023 Issue: Volume: Page:1-10
ISSN:2367-3370
Container-title:Soft Computing: Theories and Applications
language:
Short-container-title:

Author:

Sahana D.,Varsha K. S.,Sen Snigdha,Priyanka R.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-9858-4_1

Reference24 articles.

1. Snigdha S et al (2022) Astronomical big data processing using machine learning: a comprehensive review. Experiment Astron 1–43. https://doi.org/10.1007/s10686-021-09827-4

2. Sandeep VY, Sen S, Santosh K (2021) Analysing and processing of astronomical images using deep learning techniques. In: 2021 IEEE international conference on electronics, computing and communication technologies (CONNECT). IEEE. https://doi.org/10.1109/CONECCT52877.2021.9622583

3. Sen S et al (2021) Implementation of neural network regression model for faster redshift analysis on cloud-based spark platform. In: International conference on industrial, engineering and other applications of applied intelligent systems. Springer, Cham. https://doi.org/10.1007/978-3-030-79463-7_50

4. Monisha R, Sen S, Davangeri RU, Sri Lakshmi KS, Dey S (2022) An approach toward design and implementation of distributed framework for astronomical big data processing. In: Intelligent systems. Springer, Singapore, pp 267–275. https://doi.org/10.1007/978-981-19-0901-6_26

5. https://www.simplilearn.com/tutorials/deep-learning-tutorial/deep-learning-algorithm

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1. CNN-LSTM based Facial Expression Detection System;2024 5th International Conference on Image Processing and Capsule Networks (ICIPCN);2024-07-03

2. Paramount—A Hidden Markov Model Based Intelligent Voice Assistant;Proceedings of International Conference on Data Analytics and Insights, ICDAI 2023;2023

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