Searched for: subject%3A%22Feature%255C%252BExtraction%22
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Xia, Z. (author), Booij, O. (author), Kooij, J.F.P. (author)
We propose a novel end-to-end method for cross-view pose estimation. Given a ground-level query image and an aerial image that covers the query's local neighborhood, the 3 Degrees-of-Freedom camera pose of the query is estimated by matching its image descriptor to descriptors of local regions within the aerial image. The...
journal article 2024
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Vargas Quiros, J.D. (author), Kapcak, Oyku (author), Hung, H.S. (author), Cabrera Quiros, L.C. (author)
Interpersonal attraction is known to motivate behavioral responses in the person experiencing this subjective phenomenon. Such responses may involve the imitation of behavior, as in mirroring or mimicry of postures or gestures, which have been found to be associated with the desire to be liked by an interlocutor. Speed dating provides a...
journal article 2023
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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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Ren, Liyuan (author), Yarovoy, Alexander (author), Fioranelli, F. (author)
The problem of radar-based counting of multiple individuals moving as a single group is addressed using an mm-wave multiple-input-multiple-output (MIMO) frequency-modulated continuous wave (FMCW) radar. This problem is challenging because the different individuals are closer to each other than the range/azimuth resolution, and their bulk...
journal article 2023
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Li, Ruohan (author), Dong, Y. (author)
Lane detection is crucial for vehicle localization which makes it the foundation for automated driving and many intelligent and advanced driving assistant systems. Available vision-based lane detection methods do not make full use of the valuable features and aggregate contextual information, especially the interrelationships between lane...
journal article 2023
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Pandey, Pankaj (author), Rodriguez-Larios, Julio (author), Miyapuram, Krishna Prasad (author), Lomas, J.D. (author)
Electroencephalography (EEG) enables online monitoring brain activity, which can be used for neurofeedback. One of the growing applications of EEG neurofeedback is to facilitate meditation practice. Specifically, EEG neurofeedback can be used to alert participants whenever they get distracted during meditation practice based on changes in their...
conference paper 2023
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Zhang, T. (author), El Ali, Abdallah (author), Wang, Chen (author), Hanjalic, A. (author), Cesar, Pablo (author)
Instead of predicting just one emotion for one activity (e.g., video watching), fine-grained emotion recognition enables more temporally precise recognition. Previous works on fine-grained emotion recognition require segment-by-segment, fine-grained emotion labels to train the recognition algorithm. However, experiments to collect these...
journal article 2023
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Ding, Chuanwei (author), Zhang, Li (author), Chen, Haoyu (author), Hong, Hong (author), Zhu, Xiaohua (author), Fioranelli, F. (author)
Radar-based solutions have attracted great attention in human activity recognition (HAR) for their advantages in accuracy, robustness, and privacy protection. The conventional approaches transform radar signals into feature maps and then directly process them as visual images. While effective, these image-based methods may not be the best...
journal article 2023
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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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Smirnova, Alisa (author), Yang, J. (author), Yang, Dingqi (author), Cudre-Mauroux, Philippe (author)
Noisy labels represent one of the key issues in supervised machine learning. Existing work for label noise reduction mainly takes a probabilistic approach that infers true labels from data distributions in low-level feature spaces. Such an approach is not only limited by its capability to learn high-quality data representations, but also by...
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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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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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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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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Dong, 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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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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Qu, Dingran (author), Qiao, Tiezhu (author), Pang, Y. (author), Yang, Yi (author), Zhang, Haitao (author)
Belt conveyor is considered as a momentous component of modern coal mining transportation system, and thus it is an essential task to diagnose and monitor the damage of belt in real time and accurately. Based on the deep learning algorithm, this present study proposes a method of conveyor belt damage detection based on ADCN (Adaptive Deep...
journal article 2021
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Sokooti, Hessam (author), Yousefi, Sahar (author), Elmahdy, Mohamed S. (author), Lelieveldt, B.P.F. (author), Staring, M. (author)
In this paper we propose a supervised method to predict registration misalignment using convolutional neural networks (CNNs). This task is casted to a classification problem with multiple classes of misalignment: 'correct' 0-3 mm, 'poor' 3-6 mm and 'wrong' over 6 mm. Rather than a direct prediction, we propose a hierarchical approach, where...
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
Searched for: subject%3A%22Feature%255C%252BExtraction%22
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