Data imputation in deep neural network to enhance breast cancer detection
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22743
Abstract: Breast cancer is one of the most precarious cancers that claims many women's' lives every year. The existing automated systems for mammography datasets are designed to detect the abnormalities and classify them as benign or… read more here.
Keywords: data imputation; breast cancer; enhance; cancer ... See more keywords
Missing data imputation and sensor self-validation towards a sustainable operation of wastewater treatment plants via deep variational residual autoencoders.
Sign Up to like & getrecommendations! Published in 2021 at "Chemosphere"
DOI: 10.1016/j.chemosphere.2021.132647
Abstract: Missing data imputation and automatic fault detection of wastewater treatment plant (WWTP) sensors are crucial for energy conservation and environmental protection. Given the dynamic and non-linear characteristics of WWTP measurements, the conventional diagnosis models are… read more here.
Keywords: data imputation; wastewater treatment; missing data; imputation sensor ... See more keywords
Innovative method for traffic data imputation based on convolutional neural network
Sign Up to like & getrecommendations! Published in 2018 at "IET Intelligent Transport Systems"
DOI: 10.1049/iet-its.2018.5114
Abstract: The quality of traffic data is crucial for modern transportation planning and operations. However, data could be missing for various reasons. Hence, the data imputation approaches which aim at predicting/replacing the missing data or bad… read more here.
Keywords: traffic data; data imputation; method; convolutional neural ... See more keywords
Urban Traffic Data Imputation With Detrending and Tensor Decomposition
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2964299
Abstract: Due to various uncontrollable factors (such as random faulty acquisition equipment and data distortion), urban traffic flow data inevitably suffers from some form of data loss. Finding an effective filling method to estimate the missing… read more here.
Keywords: decomposition; tensor decomposition; traffic flow; traffic ... See more keywords
Mixed Data Imputation Using Generative Adversarial Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3218067
Abstract: Missing values are common in real-world datasets and pose a significant challenge to the performance of statistical and machine learning models. Generally, missing values are imputed using statistical methods, such as the mean, median, mode,… read more here.
Keywords: training data; machine learning; generative adversarial; mixed data ... See more keywords
Long Gaps Missing IoT Sensors Time Series Data Imputation: A Bayesian Gaussian Approach
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3218785
Abstract: Missing sensor data is a common problem associated with Internet of Things ecosystems, which affects the accuracy of associated services such as adequate medical intervention for older adults living at home. This problem is caused… read more here.
Keywords: missing data; approach; long gaps; data imputation ... See more keywords
Data Imputation Techniques Applied to the Smart Grids Environment
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3262188
Abstract: The electricity sector has added plenty of new technologies in recent years. Smart Grids are characterized by the use of monitoring and communication technologies almost in whole system. The application and use of such new… read more here.
Keywords: grids environment; imputation techniques; data imputation; smart grids ... See more keywords
Missing Traffic Data Imputation for Artificial Intelligence in Intelligent Transportation Systems: Review of Methods, Limitations, and Challenges
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3264216
Abstract: Missing data in Intelligent Transportation Systems (ITS) could lead to possible errors in the analyses of traffic data. Applying Artificial Intelligence (AI) in these circumstances can mitigate such problems. Past works focused only on specific… read more here.
Keywords: missing data; intelligent transportation; traffic; traffic data ... See more keywords
FIGAN: A Missing Industrial Data Imputation Method Customized for Soft Sensor Application
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Automation Science and Engineering"
DOI: 10.1109/tase.2021.3132037
Abstract: Missing data is quite common in the industrial field, resulting in problems in downstream applications, as most data driven methods used in these applications rely on complete and high-quality dataset to build a high-quality model.… read more here.
Keywords: missing data; soft sensor; downstream; data imputation ... See more keywords
Learning a Credal Classifier With Optimized and Adaptive Multiestimation for Missing Data Imputation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2021.3090210
Abstract: The classification analysis of missing data is still a challenging task since the training patterns may be insufficient and incomplete in many fields. To train a high-performance classifier and pursue high accuracy, we learn a… read more here.
Keywords: credal classifier; classifier; missing data; optimized adaptive ... See more keywords
Bayesian dynamic linear model framework for structural health monitoring data forecasting and missing data imputation during typhoon events
Sign Up to like & getrecommendations! Published in 2022 at "Structural Health Monitoring"
DOI: 10.1177/14759217221079529
Abstract: A Bayesian dynamic linear model (BDLM) framework for data modeling and forecasting is proposed to evaluate the performance of an operational cable-stayed bridge, that is, Ting Kau Bridge in Hong Kong, by using SHM strain… read more here.
Keywords: missing data; typhoon; monitoring; data imputation ... See more keywords