Searched for: subject%3A%22Features%255C%2Bextraction%22
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Barokas Profeta, Doruk (author)
The rise of streaming and video technologies has underscored the significance of efficient access and navigation of digital content, particularly for scholars in fields like history and art. Scholars actively seek streamlined approaches to index, retrieve, and explore digital content, with a focus on locating specific instances. The process of...
master thesis 2023
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van Heerde, Roald (author)
In today’s world, accurate location sensing is impossible to think away. One of the most prominent and most used techniques for determining location is GPS. In the outside world, GPS is capable of pinpointing a location with only a few meters error. But inside buildings, GPS often fails to deliver the same accuracy. In this paper, a relatively...
bachelor thesis 2023
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Boz, Artun (author)
Face clustering is a subfield of computer vision and pattern recognition with many applications such as face recognition and surveillance. Accurate clustering of faces can also help us to create labeled datasets. However, in the domain of comics, face clustering is not well studied. Therefore, it is uncertain which methods of feature extraction...
bachelor thesis 2023
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Anceaux, Duyemo (author)
Since every day more and more data is collected, it becomes more and more expensive to process. To reduce these costs, you can use dimensionality reduction to reduce the number of features per instance in a given dataset. <br/><br/>In this paper, we will compare four possible methods of dimensionality reduction. The feature extraction methods...
bachelor thesis 2023
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den Ridder, Luc (author)
Although deep reinforcement learning (DRL) is a highly promising approach to learning robotic vision-based control, it is plagued by long training times. This report introduces a DRL setup that relies on self-supervised learning for extracting depth information valuable for navigation. Specifically, a literature study is conducted to investigate...
master thesis 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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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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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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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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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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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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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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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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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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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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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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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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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
Searched for: subject%3A%22Features%255C%2Bextraction%22
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