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Li, Wanda (author), Xu, Zhiwei (author), Sun, Yi (author), Gong, Qingyuan (author), Chen, Y. (author), Ding, Aaron Yi (author), Wang, Xin (author), Hui, Pan (author)Outstanding users (OUs) denote the influential, 'core' or 'bridge' users in online social networks. How to accurately detect and rank them is an important problem for third-party online service providers and researchers. Conventional efforts, ranging from early graph-based algorithms to recent machine learning-based approaches, typically rely on...journal article 2023
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HU, YANAN (author)In recent years, the expansion of the Internet has brought an explosion of visual information, including social media, medical photographs, and digital history. This massive amount of visual content generation and sharing presents new challenges, especially when searching for similar information in databases —— Content-Based Image Retrieval ...master thesis 2022
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Xu, Weitao (author), Xue, Wanli (author), Lin, Qi (author), Lan, G. (author), Feng, Xingyu (author), Wei, Bo (author), Luo, Chengwen (author), Li, Wei (author), Zomaya, Albert Y. (author)Smart space has emerged as a new paradigm that combines sensing, communication, and artificial intelligence technologies to offer various customized services. A fundamental requirement of these services is person identification. Although a variety of person-identification approaches has been proposed, they suffer from several limitations in...journal article 2022
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Yin, Zhao (author), Geraedts, Victor Jacobus (author), Wang, Z. (author), Contarino, Maria Fiorella (author), Dibeklioglu, H. (author), van Gemert, J.C. (author)Parkinson's disease (PD) diagnosis is based on clinical criteria, i.e., bradykinesia, rest tremor, rigidity, etc. Assessment of the severity of PD symptoms with clinical rating scales, however, is subject to inter-rater variability. In this paper, we propose a deep learning based automatic PD diagnosis method using videos to assist the...journal article 2022
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Dong, Xichao (author), Zhao, Zewei (author), Wang, Yupei (author), Zeng, Tao (author), Wang, J. (author), Sui, Yi (author)Recently, frequency-modulated continuous-wave (FMCW) radar-based hand gesture recognition (HGR) using deep learning has achieved favorable performance. However, many existing methods use extracted features separately, i.e., using one of the range, Doppler, azimuth, or elevation angle information, or a combination of any two, to train...journal article 2022
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Li, Fang (author), Li, Xueyuan (author), Liu, Qi (author), Li, Z. (author)Pedestrian detection is an important branch of computer vision, and it has important applications in the fields of autonomous driving, artificial intelligence and video surveillance.With the rapid development of deep learning and the proposal of large-scale datasets, pedestrian detection has reached a new stage and achieves better performance...journal article 2022
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Sethuraman, H. Visvanathan (author), Yarovoy, Alexander (author), Fioranelli, F. (author)The ability of a fully polarimetric radar to discriminate between payloads carried by UAVs is demonstrated. A novel approach has been employed in the feature extraction algorithm, where features from individual and combined polarimetric channels are extracted for classification. Decision and ensemble fusions on the respective extracted features...conference paper 2022
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MuCoMiD: A Multitask graph Convolutional Learning Framework for miRNA-Disease Association PredictionDong, Thi Ngan (author), Mucke, Stefanie (author), Khosla, M. (author)Growing evidence from recent studies implies that microRNAs or miRNAs could serve as biomarkers in various complex human diseases. Since wet-lab experiments for detecting miRNAs associated with a disease are expensive and time-consuming, machine learning techniques for miRNA-disease association prediction have attracted much attention in...journal article 2022
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Tao, Qinghua (author), Li, Zhen (author), Xu, Jun (author), Lin, Shu (author), De Schutter, B.H.K. (author), Suykens, Johan A.K. (author)Traffic flow (TF) prediction is an important and yet a challenging task in transportation systems, since the TF involves high nonlinearities and is affected by many elements. Recently, neural networks have attracted much attention for TF prediction, but they are commonly black boxes with complex architectures and difficult to be interpreted,...journal article 2022
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Gobardhan, Rommy (author)The study of epidemic spreading processes on contact based complex networks has gained a lot of traction in recent years. These processes can entail a variety of problems such as disease spreading, opinion spreading in social networks or even airport congestion in airline networks. One of the key tasks in this area of research and also of this...master thesis 2021
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Bosma, Detmer (author)Nowadays, many practical radar applications require an automatic interpretation of the received data, including data processing algorithms and target classification. The exploitation of additional polarimetric information is a very promising concept to improve the performance of automotive target classification. In this thesis work, we aim to...master thesis 2021
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Khandhar, Shubham (author)With the ever-increasing threat of malware attacks, building an effective malware classifier to detect malware promptly is of utmost importance. Malware is constantly growing and evolving with the use of sophisticated obfuscation techniques. Thus, classifying malware accurately becomes a tough challenge. Malware visualization approaches and deep...master thesis 2021
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Visvanathan Sethuraman, Harinee (author)Unmanned Aerial Vehicles (UAVs), commonly referred to as drones have gained increasing popularity with current technological breakthroughs. Recent reports indicate the number of registered drones in the United States have crossed 850,000 and is expected to increase multi-fold over the coming years. The widespread applications of drones include...master thesis 2021
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Garack, Jonathan (author)MalPaCa is an unsupervised clustering tool, which the main purpose is to cluster unidirectional network connections based on network behavior. The clustering is only based on non-intrusive (private) packet features such as transport and network header fields, and thus it has a strong potential use-case. This paper focuses on feature extraction...bachelor thesis 2021
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Park, Sung kyung (author)Identifying novel malware and their behaviour enables security engineers to prevent and protect users with devices on the network from attackers. MalPaCA is an algorithm that helps to understand the behaviours of the network traffic by clustering uni-directional network connections which can be analyzed further to interpret which label suites...bachelor thesis 2021
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Kenesei, Kristof (author)This research concerned the design and implementation of a system to perform the 3D conversion of a national road network using airborne Lidar data and land-based road elevation measurements, preserving its topology and quantifying output elevation accuracy. While the system was designed with generality in mind, specific Dutch open data datasets...master thesis 2021
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Booij, Thomas (author)Retrieving actionable information from large datasets is increasingly computationally expensive due to the current trend of ever-increasing dataset sizes. Reducing dataset sizes with dimensionality reduction techniques is often necessary for statistical analysis techniques, such as classification, to be computationally feasible. Most...master thesis 2021
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Khedekar, Tejas (author)Movable bridge decks experience critical expansion in summer, leading to uncertainty and unpredictability in its availability doe to improper docking and safety hazard. If the bridges are not cooled soon, the inertia of expansion stays, causing prolongation of availability problems. Structural health monitoring of such bridges with a predictive...master thesis 2021
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Zhou, Zixia (author), Zu, Xinrui (author), Wang, Yuanyuan (author), Lelieveldt, Boudewijn P.F. (author), Tao, Q. (author)Embedding high-dimensional data onto a low-dimensional manifold is of both theoretical and practical value. In this article, we propose to combine deep neural networks (DNN) with mathematics-guided embedding rules for high-dimensional data embedding. We introduce a generic deep embedding network (DEN) framework, which is able to learn a...journal article 2021
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Karagoz, G. (author)We live in an era in which a myriad of computer systems produce immense amounts of (raw) data every day. This big data must be processed efficiently to gain valuable and hidden knowledge. Complex processing pipelines need to be designed for filtering out irrelevant data, also for efficient data mining and machine learning methods must be used...conference paper 2021