Seeing without Looking: Analysis Pipeline for Child Sexual Abuse Datasets-Reference-Cited by-同舟云学术

Seeing without Looking: Analysis Pipeline for Child Sexual Abuse Datasets

Published:2022-06-20 Issue: Volume: Page:
ISSN:
Container-title:2022 ACM Conference on Fairness, Accountability, and Transparency
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Author:

Laranjeira da Silva Camila¹,Macedo Joao¹,Avila Sandra²,dos Santos Jefersson¹

Affiliation:

1. Department of Computer Science, Universidade Federal de Minas Gerais, Brazil

2. Institute of Computing, Universidade Estadual de Campinas, Brazil

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3531146.3534636

Reference55 articles.

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2. Mhd Wesam Al-Nabki Eduardo Fidalgo Roberto A Vasco-Carofilis Francisco Janez-Martino and Javier Velasco-Mata. 2020. Evaluating performance of an adult pornography classifier for child sexual abuse detection. arXiv preprint arXiv:2005.08766(2020). Mhd Wesam Al-Nabki Eduardo Fidalgo Roberto A Vasco-Carofilis Francisco Janez-Martino and Javier Velasco-Mata. 2020. Evaluating performance of an adult pornography classifier for child sexual abuse detection. arXiv preprint arXiv:2005.08766(2020).

3. DeepUAge: Improving Underage Age Estimation Accuracy to Aid CSEM Investigation

4. Large image datasets: A pyrrhic win for computer vision?

5. Alexey Bochkovskiy Chien-Yao Wang and Hong-Yuan Mark Liao. 2020. Yolov4: Optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934(2020). Alexey Bochkovskiy Chien-Yao Wang and Hong-Yuan Mark Liao. 2020. Yolov4: Optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934(2020).

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