48 citations
- Beijing Jiaotong UniversityCN2 papers
- Sorbonne UniversitéFR2 papers
- Aalto UniversityFI1 paper
- Academy of AthensGR1 paper
- Applied Materials (United States)US1 paper
- Applied Mathematics (United States)US1 paper
- Assistance Publique – Hôpitaux de ParisFR1 paper
- Astronomy and SpaceAU1 paper
- AstroTec Holding (Netherlands)NL1 paper
- Atmospheric and Space Technology Research Associates (United States)US1 paper
- Beijing Normal UniversityCN1 paper
- Boston UniversityUS1 paper
6 papers
Vocabulary-Guided Gait Recognition
Panjian Huang, Saihui Hou, Chunshui Cao +2
What is a gait? Appearance-based gait networks consider a gait as the human shape and motion information from images. Model-based gait networks treat a gait as the human inherent s…
Origin of the ring ellipticity in the black hole images of M87*
Rohan Dahale, Ilje Cho, Kotaro Moriyama +273
We investigate the origin of the elliptical ring structure observed in the images of the supermassive black hole M87*, aiming to disentangle contributions from gravitational, astro…
MDE for Machine Learning-Enabled Software Systems: A Case Study and Comparison of MontiAnna & ML-Quadrat
Jörg Christian Kirchhof, Evgeny Kusmenko, Jonas Ritz +5
In this paper, we propose to adopt the MDE paradigm for the development of Machine Learning (ML)-enabled software systems with a focus on the Internet of Things (IoT) domain. We il…
The MAPT gene is differentially methylated in the progressive supranuclear palsy brain
Vincent Huin, Vincent Deramecourt, Dominique Caparros-Lefebvre +10
Background: Progressive supranuclear palsy (PSP) is a rare neurodegenerative disease causing parkinsonian symptoms. Altered DNA methylation of the microtubule-associated protein ta…
Global Norm-Aware Pooling for Pose-Robust Face Recognition at Low False Positive Rate
Sheng Chen, Jia Guo, Yang Liu +2
In this paper, we propose a novel Global Norm-Aware Pooling (GNAP) block, which reweights local features in a convolutional neural network (CNN) adaptively according to their L2 no…
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
Sheng Chen, Yang Liu, Xiang Gao +1
We present a class of extremely efficient CNN models, MobileFaceNets, which use less than 1 million parameters and are specifically tailored for high-accuracy real-time face verifi…