Machine Learning Systems: Publications

Journal papers

• [1]

  DeepTIO: A Deep Thermal−Inertial Odometry with Visual Hallucination

  M.R.U. Saputra P.P.B. de Gusmao C.X. Lu Y. Almalioglu S. Rosa C. Chen J. Wahlstrom W. Wang A. Markham and N. Trigoni

  In IEEE Robotics and Automation Letters (RAL) + IEEE ICRA. 2020.

  Details about DeepTIO: A Deep Thermal−Inertial Odometry with Visual Hallucination | BibTeX data for DeepTIO: A Deep Thermal−Inertial Odometry with Visual Hallucination | Download  (pdf) of DeepTIO: A Deep Thermal−Inertial Odometry with Visual Hallucination

• [2]

  Distilling Knowledge From a Deep Pose Regressor Network

  Muhamad Risqi U. Saputra Pedro P. B. de Gusmao Yasin Almalioglu Andrew Markham and Niki Trigoni

  In IEEE/CVF International Conference on Computer Vision (ICCV). 2019.

  Details about Distilling Knowledge From a Deep Pose Regressor Network | BibTeX data for Distilling Knowledge From a Deep Pose Regressor Network | Download of Distilling Knowledge From a Deep Pose Regressor Network

• [3]

  Learning Monocular Visual Odometry through Geometry−Aware Curriculum Learning

  Muhamad Risqi U. Saputra Pedro P. B. de Gusmao Sen Wang Andrew Markham and Niki Trigoni

  In IEEE International Conference on Robotics and Automation (ICRA). 2019.

  Details about Learning Monocular Visual Odometry through Geometry−Aware Curriculum Learning | BibTeX data for Learning Monocular Visual Odometry through Geometry−Aware Curriculum Learning | Download  (pdf) of Learning Monocular Visual Odometry through Geometry−Aware Curriculum Learning

• [4]

  GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks

  Y. Almalioglu M. R. U. Saputra P. P. de Gusmao A. Markham and N. Trigoni

  In IEEE International Conference on Robotics and Automation (ICRA). 2019.

  Details about GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks | BibTeX data for GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks | Download  (pdf) of GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks

• [5]

  DeepVO: Towards End−to−End Visual Odometry with Deep Recurrent Convolutional Neural Networks

  S. Wang‚ R. Clark‚ H. Wen and N. Trigoni

  In International Conference on Robotics and Automation. 2017.

  Details about DeepVO: Towards End−to−End Visual Odometry with Deep Recurrent Convolutional Neural Networks | BibTeX data for DeepVO: Towards End−to−End Visual Odometry with Deep Recurrent Convolutional Neural Networks | Download  (pdf) of DeepVO: Towards End−to−End Visual Odometry with Deep Recurrent Convolutional Neural Networks

Conference papers

• [1]

  Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues

  Chris Xiaoxuan Lu‚ Xuan Kan‚ Bowen Du‚ Changhao Chen‚ Hongkai Wen‚ Andrew Markham‚ Niki Trigoni and John Stankovic

  In The Web Conference (WWW). 2019.

  Details about Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues | BibTeX data for Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues | Download  (pdf) of Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues

• [2]

  Demo Abstract: Automatic Face Recognition Adaptation via Ambient Wireless Identifiers

  Chris Xiaoxuan Lu‚ Peijun Zhao‚ Bowen Du‚ Hongkai Wen‚ Andrew Markham‚ Stefano Rosa and Niki Trignoni

  In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems (SenSys). 2018.

  Details about Demo Abstract: Automatic Face Recognition Adaptation via Ambient Wireless Identifiers | BibTeX data for Demo Abstract: Automatic Face Recognition Adaptation via Ambient Wireless Identifiers | Download  (pdf) of Demo Abstract: Automatic Face Recognition Adaptation via Ambient Wireless Identifiers

• [3]

  IONet: Learning to Cure the Curse of Drift in Inertial Odometry

  Changhao Chen‚ Chris Xiaoxuan Lu‚ Andrew Markham and Niki Trigoni

  In The Thirty−Second AAAI Conference on Artificial Intelligence (AAAI−18). 2018.

  Details about IONet: Learning to Cure the Curse of Drift in Inertial Odometry | BibTeX data for IONet: Learning to Cure the Curse of Drift in Inertial Odometry | Download  (pdf) of IONet: Learning to Cure the Curse of Drift in Inertial Odometry

• [4]

  Snoopy: Sniffing Your Smartwatches Passwords via Deep Sequence Learning

  Chris Xiaoxuan Lu‚ Bowen Du‚ Hongkai Wen‚ Sen Wang‚ Andrew Markham‚ Ivan Martinovic‚ Yiran Shen and Niki Trigoni

  In ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp). 2018.

  Details about Snoopy: Sniffing Your Smartwatches Passwords via Deep Sequence Learning | BibTeX data for Snoopy: Sniffing Your Smartwatches Passwords via Deep Sequence Learning | Download slides.key of Snoopy: Sniffing Your Smartwatches Passwords via Deep Sequence Learning | Download [UbiComp2018]snoopy.pdf of Snoopy: Sniffing Your Smartwatches Passwords via Deep Sequence Learning

• [5]

  VINet: Visual Inertial Odometry as a Sequence to Sequence Learning Problem

  R. Clark‚ S. Wang‚ H. Wen‚ A. Markham and N. Trigoni

  In AAAI Conference on Artificial Intelligence (AAAI). 2017.

  Details about VINet: Visual Inertial Odometry as a Sequence to Sequence Learning Problem | BibTeX data for VINet: Visual Inertial Odometry as a Sequence to Sequence Learning Problem | Download  (pdf) of VINet: Visual Inertial Odometry as a Sequence to Sequence Learning Problem

• [6]

  SCAN: Learning Speaker Identity From Noisy Sets of Sensor Data

  Chris Xiaoxuan Lu‚ Hongkai Wen‚ Sen Wang‚ Andrew Markham and Niki Trigoni

  In ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). 2017.

  Details about SCAN: Learning Speaker Identity From Noisy Sets of Sensor Data | BibTeX data for SCAN: Learning Speaker Identity From Noisy Sets of Sensor Data | Download  (pdf) of SCAN: Learning Speaker Identity From Noisy Sets of Sensor Data

• [7]

  VidLoc: A Deep Spatio−Temporal Model for 6−DoF Video−Clip Relocalization

  Ronald Clark‚ Sen Wang‚ Andrew Markham‚ Niki Trigoni and Hongkai Wen

  In Computer Vision and Pattern Recognition (CVPR). 2017.

  Details about VidLoc: A Deep Spatio−Temporal Model for 6−DoF Video−Clip Relocalization | BibTeX data for VidLoc: A Deep Spatio−Temporal Model for 6−DoF Video−Clip Relocalization | Download  (pdf) of VidLoc: A Deep Spatio−Temporal Model for 6−DoF Video−Clip Relocalization

• [8]

  "Gabor filter based image representation for object classification."

  Gianluca. Rizvi S.T.H.; Cabodi Gianpiero; P. B. de Gusmao Pedro; Francini

  2016.

  Details about "Gabor filter based image representation for object classification." | BibTeX data for "Gabor filter based image representation for object classification." | DOI (10.1109/CoDIT.2016.7593635)