Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Brophy, Eoin"'
Network and system security are incredibly critical issues now. Due to the rapid proliferation of malware, traditional analysis methods struggle with enormous samples. In this paper, we propose four easy-to-extract and small-scale features, including
Externí odkaz:
http://arxiv.org/abs/2201.07649
Continuous medical time series data such as ECG is one of the most complex time series due to its dynamic and high dimensional characteristics. In addition, due to its sensitive nature, privacy concerns and legal restrictions, it is often even comple
Externí odkaz:
http://arxiv.org/abs/2111.00314
Bitcoin is firmly becoming a mainstream asset in our global society. Its highly volatile nature has traders and speculators flooding into the market to take advantage of its significant price swings in the hope of making money. This work brings an al
Externí odkaz:
http://arxiv.org/abs/2110.14936
Sensitive medical data is often subject to strict usage constraints. In this paper, we trained a generative adversarial network (GAN) on real-world electronic health records (EHR). It was then used to create a data-set of "fake" patients through synt
Externí odkaz:
http://arxiv.org/abs/2109.02543
Generative adversarial networks (GANs) studies have grown exponentially in the past few years. Their impact has been seen mainly in the computer vision field with realistic image and video manipulation, especially generation, making significant advan
Externí odkaz:
http://arxiv.org/abs/2107.11098
Ischemic heart disease is the highest cause of mortality globally each year. This not only puts a massive strain on the lives of those affected but also on the public healthcare systems. To understand the dynamics of the healthy and unhealthy heart d
Externí odkaz:
http://arxiv.org/abs/2102.12245
Autor:
She, Qi, Feng, Fan, Liu, Qi, Chan, Rosa H. M., Hao, Xinyue, Lan, Chuanlin, Yang, Qihan, Lomonaco, Vincenzo, Parisi, German I., Bae, Heechul, Brophy, Eoin, Chen, Baoquan, Graffieti, Gabriele, Goel, Vidit, Han, Hyonyoung, Kanagarajah, Sathursan, Kumar, Somesh, Lam, Siew-Kei, Lam, Tin Lun, Ma, Liang, Maltoni, Davide, Pellegrini, Lorenzo, Piyasena, Duvindu, Pu, Shiliang, Sheet, Debdoot, Song, Soonyong, Son, Youngsung, Wang, Zhengwei, Ward, Tomas E., Wu, Jianwen, Wu, Meiqing, Xie, Di, Xu, Yangsheng, Yang, Lin, Zhong, Qiaoyong, Zhou, Liguang
This report summarizes IROS 2019-Lifelong Robotic Vision Competition (Lifelong Object Recognition Challenge) with methods and results from the top $8$ finalists (out of over~$150$ teams). The competition dataset (L)ifel(O)ng (R)obotic V(IS)ion (OpenL
Externí odkaz:
http://arxiv.org/abs/2004.14774
Wrist-worn smart devices are providing increased insights into human health, behaviour and performance through sophisticated analytics. However, battery life, device cost and sensor performance in the face of movement-related artefact present challen
Externí odkaz:
http://arxiv.org/abs/2004.00505
Access to medical data is highly restricted due to its sensitive nature, preventing communities from using this data for research or clinical training. Common methods of de-identification implemented to enable the sharing of data are sometimes inadeq
Externí odkaz:
http://arxiv.org/abs/1909.09150
In the recent years Generative Adversarial Networks (GANs) have demonstrated significant progress in generating authentic looking data. In this work we introduce our simple method to exploit the advancements in well established image-based GANs to sy
Externí odkaz:
http://arxiv.org/abs/1902.05624