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Found 6 papers, 1 papers with code
Safe machine learning model release from Trusted Research Environments: The AI-SDC package
We present AI-SDC, an integrated suite of open source Python tools to facilitate Statistical Disclosure Control (SDC) of Machine Learning (ML) models trained on confidential data prior to public release.
GRAIMATTER Green Paper: Recommendations for disclosure control of trained Machine Learning (ML) models from Trusted Research Environments (TREs)
This is a complex topic, and it is unreasonable to expect all TREs to be aware of all risks or that TRE researchers have addressed these risks in AI-specific training.
Machine Learning Models Disclosure from Trusted Research Environments (TRE), Challenges and Opportunities
In this paper we introduce the challenge of disclosing trained machine learning models from TREs.
Forward and Inverse models in HCI:Physical simulation and deep learning for inferring 3D finger pose
We infer finger 3D position $(x, y, z)$ and pose (pitch and yaw) on a mobile device using capacitive sensors which can sense the finger up to 5cm above the screen.
Single-Shot Clothing Category Recognition in Free-Configurations with Application to Autonomous Clothes Sorting
Our visual feature is robust to deformable shapes and our approach is able to recognise the category of unknown clothing in unconstrained and random configurations.
Robot Vision Architecture for Autonomous Clothes Manipulation
The experimental results show that the proposed dual-arm flattening using stereo vision system remarkably outperforms the single-arm flattening and widely-cited Kinect-based sensing system for dexterous manipulation tasks.
