Subhaluxmi Sahoo, Pradipta Kumar Nanda,
... main novelties of our paper are: (i) ST-KDE based background modeling, (ii) Determination of the weights of the fusion process in an adaptive framework and, (iii) online background model learning in feature ...
Tópico(s): Image Enhancement Techniques
2021 - Institute of Electrical and Electronics Engineers | IEEE Transactions on Circuits and Systems for Video Technology
Xin Chen, Ratnasingham Tharmarasa, T. Kirubarajan, Mike McDonald,
... method is developed under the kernel density estimation (KDE) framework to estimate the spatial intensity of false alarms ...
Tópico(s): Indoor and Outdoor Localization Technologies
2014 - Institution of Engineering and Technology | IET Radar Sonar & Navigation
... understanding and the broad applicability of a CTE–KDE framework. It applies this framework to 6 food sectors ...
Tópico(s): Meat and Animal Product Quality
2014 - Wiley | Comprehensive Reviews in Food Science and Food Safety
Johan Medrano, Abderrahmane Kheddar, Annick Lesne, Sofiane Ramdani,
... Estimator (KDE) related to the correlation sum. The KDE framework provides non-parametric tools to approximate a density function from finite samples (e.g., histograms) and optimal methods to select a smoothing parameter, the bandwidth (e.g., bin width in histograms). We use results from KDE to derive a closed-form expression for the ...
Tópico(s): Fractal and DNA sequence analysis
2021 - American Institute of Physics | Chaos An Interdisciplinary Journal of Nonlinear Science
Ruo Du, Qiang Wu, Xiangjian He, Jie Yang,
... KDE (kernel density estimation)+mean shift". Since the KDE+mean shift framework is an unsupervised learning method, we extend KDE to its supervised version, called supervised KDE (SKDE), ...
Tópico(s): Video Analysis and Summarization
2012 - Elsevier BV | Signal Processing
... wave height prediction interval. The proposed LSTM-GRU-KDE forecasting framework is compared with benchmark models to verify its ...
Tópico(s): Hydrological Forecasting Using AI
2023 - Elsevier BV | Ocean Engineering
Lei Zhang, Lun Xie, Qinkai Han, Zhiliang Wang, Chen Huang,
... on quantile regression (QR) and kernel density estimation (KDE), a framework for probability density forecasting of short-term wind ...
Tópico(s): Wind Energy Research and Development
2020 - Multidisciplinary Digital Publishing Institute | Energies
Zixiao Zong, Mengwei Yang, Justin Ley, Athina Markopoulou, Carter T. Butts,
... raising privacy concerns. Here, we propose a Federated KDE framework for estimating the user population density, which not only keeps location data on the devices but also provides probabilistic privacy guarantees against a malicious server that tries to infer users' location. Our approach Federated random Fourier feature (RFF) KDE leverages a random feature representation of the KDE ...
Tópico(s): Data-Driven Disease Surveillance
2023 - De Gruyter Open | Proceedings on Privacy Enhancing Technologies
Lingxiao Ying, Zehao Shen, Jiding Chen, Rui Fang, Xueping Chen, Rui Jiang,
... road development priority (RDP). Based on the modified KDE model and the framework of RDP evaluation, this study provided a useful ...
Tópico(s): Environmental and Social Impact Assessments
2014 - Science Press | Chinese Geographical Science
Jeong-Seok Lee, Hyeong-Tak Lee, Ik-Soon Cho,
... ocean area are compared. Finally, the result of KDE 90% of maritime traffic with framework analyzed the safety route, which can be a ...
Tópico(s): Maritime Security and History
2022 - Institute of Electrical and Electronics Engineers | IEEE Access
Ming Li, Changqin Huang, Dianhui Wang,
... analytics, and further indicate that our proposed RSCN framework (both RSC-KDE and RSC-MCC) has a good potential for ...
Tópico(s): Face and Expression Recognition
2018 - Elsevier BV | Information Sciences
Richa Sharma, Charles R. Hurburgh, Gretchen A. Mosher,
... fail. Vulnerability analysis of an evidence‐based CTE–KDE framework accounts for complex interactions among supply chain participants' ...
Tópico(s): Meat and Animal Product Quality
2022 - Wiley | Cereal Chemistry
Myungsoo Kim, Jaehyeong Lee, Chaegyu Lee, Jongpil Jeong,
Over the last decade, the development of machine-learning models has enabled the design of sophisticated regression models. For this reason, studies have been conducted to design predictive models using machine learning in various industries. In particular, in terms of inventory management, forecasting models predict historical market demand, predict future demand, and enable systematic inventory management. However, in most small and medium enterprise (SMEs), there is no systematic management of ...
Tópico(s): Stock Market Forecasting Methods
2022 - Multidisciplinary Digital Publishing Institute | Applied Sciences
Guian Zhang, Zhiyong Yuan, Qianqian Tong, Mianlun Zheng, Jianhui Zhao,
... paper, we propose a novel image background subtraction framework based on KDE. Firstly a new data structure called Mino Vector ( ...
Tópico(s): Human Pose and Action Recognition
2018 - Elsevier BV | Pattern Recognition
Huijie Qiao, Luis E. Escobar, Erin E. Saupe, Liqiang Ji, Jorge Soberón,
... We had log-transformed the data when constructing KDE hypervolumes following the log-transformed data framework in the ‘hypervolume’ R package demo code (see ...
Tópico(s): Ecology and Vegetation Dynamics Studies
2017 - Wiley | Global Ecology and Biogeography
Marangely Gonzalez Cruz, E. Annette Hernandez, Venkatesh Uddameri,
A bivariate kernel density estimation (KDE) method was utilized to develop a stochastic framework to assess how agricultural droughts are related to unfavorable meteorological conditions. KDE allows direct estimation of the bivariate cumulative density function ...
Tópico(s): Hydrology and Watershed Management Studies
2020 - Multidisciplinary Digital Publishing Institute | Water
Dongxiao Niu, Lijie Sun, Min Yu, Keke Wang,
... kernel density estimation with the Gaussian kernel function (KDE-Gaussian). The proposed FS-GWO-VMD-BiLSTM-Attention forecasting framework is compared with benchmark models to verify its practicability and reliability. Compared with the BPNN, the mean absolute error, mean absolute percentage error, and mean square error of the FS-GWO-VMD-BiLSTM-Attention model are reduced by 94.03%, 85.82%, and 99.51%, respectively. Furthermore, according to the coverage width-based criterion, KDE-Gaussian is superior to other interval forecasting methods, ...
Tópico(s): Electric Power System Optimization
2022 - Elsevier BV | Energy
Umut Özertem, Ismail Uysal, Deniz Erdoğmuş,
... estimator is compared with the kernel density estimation (KDE)-based entropy estimator in the supervised neural network training framework with computation time and performance comparisons.
Tópico(s): Image and Signal Denoising Methods
2008 - Institute of Electrical and Electronics Engineers | IEEE Transactions on Neural Networks
Nan Ma, Kui Xu, Xiaochen Xia, Chen Wei, Qiao Su, Maiying Shen, Wei Xie,
... EJSS) is first estimated via kernel density estimation (KDE). Then, utilizing the EJSS, a deep deterministic policy gradient (DDPG) based framework is proposed to acquire the power control strategy ...
Tópico(s): Advanced MIMO Systems Optimization
2022 - IEEE Communications Society | IEEE Communications Letters
Ekaterina Plesovskaya, Sergey Ivanov,
... paper aims to analyze the generation capability of KDE-based models by evaluating their samples. For this purpose, we introduce a framework for synthetic dataset quality estimation which also accounts for the overfitting of a generative model. The performance of KDE is analyzed on samples from theoretical distributions and ...
Tópico(s): Gaussian Processes and Bayesian Inference
2021 - Elsevier BV | Procedia Computer Science
... Imaging Radiometer Suite (VIIRS). We applied an analyzing framework combing kernel density estimation (KDE) under different search radii and threshold-based extraction ...
Tópico(s): Urban Green Space and Health
2021 - Multidisciplinary Digital Publishing Institute | Remote Sensing
Shuai Wang, Gang Xu, Guo Qingsheng,
... km searching radiuses), which were transformed into raster frameworks using kernel density estimation (KDE) for correlation analysis. Global closeness and straightness are ...
Tópico(s): Urban Transport and Accessibility
2018 - Multidisciplinary Digital Publishing Institute | ISPRS International Journal of Geo-Information
Matt Higger, Murat Akçakaya, Hooman Nezamfar, Gerald LaMountain, Umut Orhan, Deniz Erdoğmuş,
... MAP) classifiers by using a Kernel Density Estimate (KDE) to learn the distribution of features conditioned on stimulation class. To demonstrate our framework we extend Canonical Correlation Analysis (CCA) and Power ... the class associated with the maximum feature. Our framework increases performance by relaxing the assumption that a stimulation class's sample often maximizes its class-associated feature. Further, by leveraging the KDE, we present a method which estimates the performance ...
Tópico(s): Neural dynamics and brain function
2014 - Institute of Electrical and Electronics Engineers | IEEE Signal Processing Letters
... 1-layer J-PET scanner in the GATE framework [5] and reconstructed using multivariate KDE from the “ks” package, developed for R software ...
Tópico(s): Digital Radiography and Breast Imaging
2018 - Springer Science+Business Media | EJNMMI Physics
... practice. In this paper, we develop an inference framework on the modality of a KDE under multivariate setting using Gaussian kernel. We applied ...
Tópico(s): Gene expression and cancer classification
2014 - Scientific Research Publishing | Open Journal of Statistics
Zhaolin Wang, Ling Ou, Meng Chen,
... factors and economic activities. This study established a framework and adopted Kernel Density Estimation (KDE), Exploratory Spatial Data Analysis (ESDA), Geographical detector (Geo- ...
Tópico(s): Urbanization and City Planning
2023 - Elsevier BV | Ecological Indicators
Chao Wu, Xinyue Ye, Fu Ren, Qingyun Du,
... period as a proxy for urban vibrancy. A framework that incorporates kernel density estimation (KDE), geographically and temporally weighted regression (GTWR) and the ...
Tópico(s): Impact of Light on Environment and Health
2018 - Elsevier BV | Cities
Mahmmadsufiyan Shaik, D. N. Gaonkar, Ramakrishna S S Nuvvula, S. M. Muyeen, Sk. A. Shezan, GM Shafiullah,
... PEM, combining the Nataf transformation, Kernel density estimation (KDE), and cubic spline interpolation. This innovative integration effectively manages wind power correlation within the analytical framework. By incorporating spline interpolation and kernel density estimation ...
Tópico(s): Power System Reliability and Maintenance
2023 - Elsevier BV | Expert Systems with Applications
Xu‐Yang Cao, De‐Cheng Feng, Michael Beer,
... researchers. In this paper, a kernel density estimation (KDE) based non-parametric cloud approach is proposed for efficient seismic fragility estimation of structures under non-stationary excitation. First, the methodology framework of the efficient approach is illustrated. Then, the procedures of non-stationary stochastic seismic response of structures and KDE-based non-parametric cloud approach for efficient seismic ...
Tópico(s): Structural Health Monitoring Techniques
2023 - Elsevier BV | Mechanical Systems and Signal Processing
Daniel J. Nieves, Jeremy A. Pike, Florian Levet, David J. Williamson, Mohammed Baragilly, Sandra Oloketuyi, Ario de Marco, Juliette Griffié, Daniel Sage, Edward A. K. Cohen, Jean‐Baptiste Sibarita, Mike Heilemann, Dylan M. Owen,
... simulated conditions mimicking experimental data. We demonstrate the framework using seven diverse analysis algorithms: DBSCAN, ToMATo, KDE, FOCAL, CAML, ClusterViSu and SR-Tesseler. Given that ...
Tópico(s): Cell Image Analysis Techniques
2023 - Nature Portfolio | Nature Methods