J
Jesus Martinez del Rincon
Researcher at Queen's University Belfast
Publications - 77
Citations - 1917
Jesus Martinez del Rincon is an academic researcher from Queen's University Belfast. The author has contributed to research in topics: Deep learning & Computer science. The author has an hindex of 13, co-authored 68 publications receiving 1335 citations. Previous affiliations of Jesus Martinez del Rincon include Kingston University.
Papers
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Proceedings ArticleDOI
Recurrent Convolutional Network for Video-Based Person Re-identification
TL;DR: A novel recurrent neural network architecture for video-based person re-identification that makes use of colour and optical flow information in order to capture appearance and motion information which is useful for video re- identification.
Proceedings ArticleDOI
Deep Android Malware Detection
Niall McLaughlin,Jesus Martinez del Rincon,BooJoong Kang,Suleiman Y. Yerima,Paul Miller,Sakir Sezer,Yeganeh Safaei,Erik Trickel,Ziming Zhao,Adam Doupé,Gail-Joon Ahn +10 more
TL;DR: A novel android malware detection system that uses a deep convolutional neural network (CNN) to perform static analysis of the raw opcode sequence from a disassembled program, removing the need for hand-engineered malware features.
Journal ArticleDOI
Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data
TL;DR: A novel Continuous Locality Preserving Projections (CLPP) technique is proposed which allows the modelling of the continuous nature of the produced in-house admixtures as data series instead of discrete points.
Proceedings ArticleDOI
Data-augmentation for reducing dataset bias in person re-identification
TL;DR: It is shown that use of data augmentation can improve the cross-dataset generalisation of convolutional network based re-identification systems, and that changing the image background yields further improvements.
Journal ArticleDOI
Development and field testing of a vision based displacement system using a low cost wireless action camera
Darragh Lydon,Myra Lydon,Su Taylor,Jesus Martinez del Rincon,David Hester,James M. W. Brownjohn +5 more
TL;DR: A contactless, low cost vision-based system for displacement measurement of civil structures which is rapidly deployable in the field and does not require direct contact or access to the infrastructure or its vicinity is introduced.