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
Multiple Data Imputation Methods Advance Risk Analysis and Treatability of Co-occurring Inorganic Chemicals in Groundwater
Sign Up to like & getrecommendations! Published in 2024 at "Environmental Science & Technology"
DOI: 10.1021/acs.est.4c05203
Abstract: Accurately assessing and managing risks associated with inorganic pollutants in groundwater is imperative. Historic water quality databases are often sparse due to rationale or financial budgets for sample collection and analysis, posing challenges in evaluating… read more here.
Keywords: data imputation; data sets; analysis; multiple data ... 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
A novel weighted-guided tensor completion missing data imputation method for health monitoring data of planar parallel mechanism
Sign Up to like & getrecommendations! Published in 2024 at "Measurement Science and Technology"
DOI: 10.1088/1361-6501/ad7623
Abstract: High-end mechanical equipment plays a crucial role in the manufacturing industry, making the monitoring of its operational status highly significant. Due to various factors such as environmental influences, the absence of monitoring signals in mechanical… read more here.
Keywords: data imputation; tensor; imputation method; missing data ... 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
A Diffusion-Based Expectation–Maximization Framework for Probabilistic Traffic Data Imputation
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2025.3594996
Abstract: Traffic data imputation plays a crucial role in supporting the development of accurate forecasting models and the provision of reliable real-time information systems. Recent advances in generative modeling, particularly diffusion models, have introduced new solutions… read more here.
Keywords: data imputation; framework; traffic data; imputation ... See more keywords