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Deep Learning-Based Detection of Inappropriate Speech Content for Film Censorship

  • Published:2022 Issue: Volume:10 Page:101697-101715
  • ISSN:2169-3536
  • Container-title:IEEE Access
  • language:
  • Short-container-title:IEEE Access

Author:

Wazir Abdulaziz Saleh Ba1ORCID,Karim Hezerul Abdul1ORCID,Lyn Hor Sui1,Ahmad Fauzi Mohammad Faizal1ORCID,Mansor Sarina1ORCID,Lye Mohd Haris1ORCID

Affiliation:

1. Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia

Funder

Telekom Malaysia (TM) Research and Development, Malaysia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference74 articles.

1. ImageNet classification with deep convolutional neural networks;krizhevsky;Commun ACM,2012

2. Rethinking the Inception Architecture for Computer Vision

3. MobileNets: Efficient convolutional neural networks for mobile vision applications;howard;arXiv 1704 04861,2017

4. Profanity Detection and Removal in Videos using Machine Learning

5. Deep Residual Learning for Image Recognition

Cited by 3 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. Inappropriate Text Detection and Rephrasing Using NLP;Communications in Computer and Information Science;2024

2. Machine Learning Approaches for Film Censorship: A Comprehensive Survey of Techniques;Lecture Notes in Networks and Systems;2024

3. Machine-Learning-Based Profanity Detection and Removal in Cartoons Videos;2023 5th International Conference on Control and Robotics (ICCR);2023-11-23
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