Results 161 to 170 of about 1,797 (204)

CSAM‐SMCA 2022 Scientific conference and annual meeting

The American Journal on Addictions, 2022
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Testing a hybrid risk assessment model: Predicting CSAM offender risk from digital forensic artifacts.

International Journal of Child Abuse & Neglect
BACKGROUND Recent research argues for a formalized hybrid risk assessment model that combines the current online child sex abuse risk measures with digital forensics artifacts.
Kathryn C. Seigfried-Spellar, Marcus K. Rogers, Nina L. Matulis, Jacob S. Heasley   +3 more
semanticscholar   +1 more source

Detecting sexually explicit content in the context of the child sexual abuse materials (CSAM): end-to-end classifiers and region-based networks

PKDD/ECML Workshops
Child sexual abuse materials (CSAM) pose a significant threat to the safety and well-being of children worldwide. Detecting and preventing the distribution of such materials is a critical task for law enforcement agencies and technology companies.
Weronika Gutfeter, Joanna Gajewska, Andrzej Pacut   +2 more
semanticscholar   +1 more source

A novel deep learning model CSAM-ResNet based on attention mechanism and residual learning for breast histopathology image classification

International Conference on Computer Supported Cooperative Work in Design
Histopathological image analysis is the gold standard for breast cancer diagnosis. In recent years, the pathological image recognition technology based on deep learning has attracted great attention.
Ruizheng Shi, Xiangru Li, Haokai Gao
semanticscholar   +1 more source

(415) THE BRIDGE PROJECT: USING CULTURAL INTERVIEW FORMULATION (CFI) TO ADAPT ONLINE INTERVENTIONS FOR CSAM USERS

Journal of Sexual Medicine
The BRIDGE intervention-research project is exploring the perceptions of anonymous CSAM users on their material using, their need for specialist care, their experiences of seeking care, and also intervenes with time-limited online interventions ...
Leona Šímová, K. Klapilová, Prof Jozef Metenko, Nina Vaaranen-Valkonen, Prof Rafael Ballester-Arnal, Peer Briken, C. Rahm   +6 more
semanticscholar   +1 more source

Colorectal Cancer Target Screening Based on the CSAM-YOLO Algorithm

2024 8th Asian Conference on Artificial Intelligence Technology (ACAIT)
Colorectal cancer is a malignant tumor that poses a serious threat to human health. Screening for colorectal tumors from abdominal CT images is a common task for radiologists. However, utilizing non-enhanced CT scans without bowel preparation or contrast
Jing Qin, Jianqiang Jin, Zumin Wang, Wencai Weng, Qi Ai, Bo Wang   +5 more
semanticscholar   +1 more source

Supporting Mobile Instructional Design with CSAM

2017
Teachers’ proficiency with emerging technologies has been identified as a cornerstone of a well-rounded modern curriculum that includes the development of students’ digital literacy skills. The central role of teachers’ technical knowledge is one of the bases of the Technological Pedagogical Content Knowledge (TPACK) framework (Koehler & Mishra in ...
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The Relationship Between a CSAM Warning Messaging Chatbot and User Behavior on Pornhub

Victims & Offenders
Child sexual abuse material (CSAM) is commonly searched for on the open web. This study evaluates the reThink chatbot that was integrated into a warning message page on Pornhub in the United Kingdom (UK).
J. Scanlan, Lauren C. Hall, Paul A. Watters, Richard Wortley, J. Prichard   +4 more
semanticscholar   +1 more source

CSAM Desistance via AI, Chatbots and Automated Warnings

Electronics
Automated warning messages for child sexual abuse material (CSAM) desistance are scalable, real-time digital interventions designed to interrupt user behaviors associated with the search for, access to, consumption, or distribution of CSAM by delivering ...
Paul A. Watters, J. Scanlan, J. Prichard, Richard Wortley   +3 more
semanticscholar   +1 more source

Generative ML and CSAM: Implications and Mitigations

A joint report between the Stanford Internet Observatory and Thorn examines implications of fully realistic child sexual abuse material (CSAM) produced by generative machine learning models. Advances in the open-source generative ML community have led to increasingly realistic adult content, to the point that content indistinguishable from actual ...
Thiel, David, Stroebel, Melissa, Portnoff, Rebecca, Hancock, Jeffrey, Scyphers, Cassandra, O'Gorman, Tim, DiResta, Renée   +6 more
openaire   +1 more source