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20182022
most citedMobile Sensor Data Anonymization

277 citations · 930 across the 33 of their papers we have counts for

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Showing 2018Show all

6 papers · 1 filter

cs.CV2018★ 1 cited

Concealing the identity of faces in oblique images with adaptive hopping Gaussian mixtures

Omair Sarwar, Bernhard Rinner, Andrea Cavallaro

Cameras mounted on Micro Aerial Vehicles (MAVs) are increasingly used for recreational photography. However, aerial photographs of public places often contain faces of bystanders t…

cs.LG2018★ 277 cited

Mobile Sensor Data Anonymization

Mohammad Malekzadeh, Richard G. Clegg, Andrea Cavallaro +1

Motion sensors such as accelerometers and gyroscopes measure the instant acceleration and rotation of a device, in three dimensions. Raw data streams from motion sensors embedded i…

cs.CV2018★ 9 cited

Video Summarisation by Classification with Deep Reinforcement Learning

Kaiyang Zhou, Tao Xiang, Andrea Cavallaro

Most existing video summarisation methods are based on either supervised or unsupervised learning. In this paper, we propose a reinforcement learning-based weakly supervised method…

cs.CV2018

A Multi-perspective Approach To Anomaly Detection For Self-aware Embodied Agents

Mohamad Baydoun, Mahdyar Ravanbakhsh, Damian Campo +5

This paper focuses on multi-sensor anomaly detection for moving cognitive agents using both external and private first-person visual observations. Both observation types are used t…

cs.LG2018

Distributed One-class Learning

Ali Shahin Shamsabadi, Hamed Haddadi, Andrea Cavallaro

We propose a cloud-based filter trained to block third parties from uploading privacy-sensitive images of others to online social media. The proposed filter uses Distributed One-Cl…

cs.LG2018★ 153 cited

Protecting Sensory Data against Sensitive Inferences

Mohammad Malekzadeh, Richard G. Clegg, Andrea Cavallaro +1

There is growing concern about how personal data are used when users grant applications direct access to the sensors of their mobile devices. In fact, high resolution temporal data…