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Publication search results
found 40 matches
- 2024
- Juan Martín, José A. Sáez, Emilio Corchado:
Tackling the problem of noisy IoT sensor data in smart agriculture: Regression noise filters for enhanced evapotranspiration prediction. Expert Syst. Appl. 237(Part B): 121608 (2024) - 2023
- Adrian Lopez Rodriguez, Benjamin Busam, Krystian Mikolajczyk:
Project to Adapt: Domain Adaptation for Depth Completion from Noisy and Sparse Sensor Data. Int. J. Comput. Vis. 131(3): 796-812 (2023) - Bryan Rodriguez, Prasanna Rangarajan, Xinxiang Zhang, Dinesh Rajan:
Dimensioning Cuboid and Cylindrical Objects Using Only Noisy and Partially Observed Time-of-Flight Data. Sensors 23(21): 8673 (2023) - Rahul Mishra, Ashish Gupta, Hari Prabhat Gupta:
Locomotion Mode Recognition Using Sensory Data With Noisy Labels: A Deep Learning Approach. IEEE Trans. Mob. Comput. 22(6): 3460-3471 (2023) - Shohei Yamanaka, Kosuke Shima, Atsuko Mutoh, Koichi Moriyama, Tohgoroh Matsui, Nobuhiro Inuzuka:
Evaluation System for Martial Arts Demonstration from Smartphone Sensor Data Using Deep Neural Networks on Noisy Labels. ICCE 2023: 1-5 - Reza Sameni:
Notes on Information Propagation in Noisy Multichannel Data Models: Insights into Sensor Selection and Fusion in Multimodal Biomedical Applications. CoRR abs/2312.15725 (2023) - 2022
- Md. Azim Ullah, Soujanya Chatterjee, Christopher P. Fagundes, Cho Lam, Inbal Nahum-Shani, James M. Rehg, David W. Wetter, Santosh Kumar:
mRisk: Continuous Risk Estimation for Smoking Lapse from Noisy Sensor Data with Incomplete and Positive-Only Labels. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6(3): 143:1-143:29 (2022) - Adar Kahana, Eli Turkel, Shai Dekel, Dan Givoli:
A physically-informed deep-learning model using time-reversal for locating a source from sparse and highly noisy sensors data. J. Comput. Phys. 470: 111592 (2022) - Sung-Jun Min, Young-Su Jo, Suk-Ju Kang:
Super-Resolving Methodology for Noisy Unpaired Datasets. Sensors 22(20): 8003 (2022) - Honghao Zeng, Shihong Jiang, Tianxiang Cui, Zheng Lu, Jiawei Li, Boon-Giin Lee, Junsong Zhu, Xiaoying Yang:
ScatterHough: Automatic Lane Detection from Noisy LiDAR Data. Sensors 22(14): 5424 (2022) - Yanming Zang, Hongyan Zhu:
Fast and optimal joint decision and estimation by quantized data via noisy channels of sensor networks. Signal Process. 195: 108481 (2022) - Matthias Kahr, Gabor Kovács, Hubert Brückl:
Fault Size Estimation of Ball Bearings: A Machine Learning Approach for Noisy Data. IEEE SENSORS 2022: 1-4 - 2021
- Emmanuel Pintelas, Ioannis E. Livieris, Panagiotis E. Pintelas:
A Convolutional Autoencoder Topology for Classification in High-Dimensional Noisy Image Datasets. Sensors 21(22): 7731 (2021) - 2020
- Christian Reich:
Learning machine monitoring models from sparse and noisy sensor data annotations (Lernen von Modellen zur Maschinenüberwachung aus spärlichen und verrauschten Sensordatenannotationen). Siegen University, Germany, 2020 - Biying Yan, Chao Yang, Pan Deng, Qiao Sun, Feng Chen, Yang Yu:
A Spatiotemporal Causality Based Governance Framework for Noisy Urban Sensory Data. J. Comput. Sci. Technol. 35(5): 1084-1098 (2020) - Chatura Seneviratne, Patikiri Arachchige Don Shehan Nilmantha Wijesekara, Henry Leung:
Performance Analysis of Distributed Estimation for Data Fusion Using a Statistical Approach in Smart Grid Noisy Wireless Sensor Networks. Sensors 20(2): 567 (2020) - Dan Stefanoiu, Janetta Culita:
Joint Stochastic Spline and Autoregressive Identification Aiming Order Reduction Based on Noisy Sensor Data. Sensors 20(18): 5038 (2020) - Adrian Lopez Rodriguez, Benjamin Busam, Krystian Mikolajczyk:
Project to Adapt: Domain Adaptation for Depth Completion from Noisy and Sparse Sensor Data. ACCV (1) 2020: 330-348 - Shizhuo Deng, Wen Hua, Botao Wang, Guoren Wang, Xiaofang Zhou:
Few-Shot Human Activity Recognition on Noisy Wearable Sensor Data. DASFAA (2) 2020: 54-72 - Aufar Zakiev, Tatyana Tsoy, Ksenia Shabalina, Evgeni Magid, Subir Kumar Saha:
Virtual Experiments on ArUco and AprilTag Systems Comparison for Fiducial Marker Rotation Resistance under Noisy Sensory Data. IJCNN 2020: 1-6 - Adrian Lopez Rodriguez, Benjamin Busam, Krystian Mikolajczyk:
Project to Adapt: Domain Adaptation for Depth Completion from Noisy and Sparse Sensor Data. CoRR abs/2008.01034 (2020) - Akram Hussain:
Decentralized Source Localization Using Wireless Sensor Networks from Noisy Data. CoRR abs/2009.01062 (2020) - 2019
- Chris Xiaoxuan Lu, Yuanbo Xiangli, Peijun Zhao, Changhao Chen, Niki Trigoni, Andrew Markham:
Autonomous Learning of Speaker Identity and WiFi Geofence From Noisy Sensor Data. IEEE Internet Things J. 6(5): 8284-8295 (2019) - Xiaoxia Song, Yong Li, Wenmei Nie:
Noisy Data Gathering in Wireless Sensor Networks via Compressed Sensing and Cross Validation. CWSN 2019: 101-111 - 2018
- Manuel S. Stein, Markus Neumayer, Kurt Barbé:
Data-Driven Quality Assessment of Noisy Nonlinear Sensor and Measurement Systems. IEEE Trans. Instrum. Meas. 67(7): 1668-1678 (2018) - Tsuyoshi Idé:
Collaborative Anomaly Detection on Blockchain from Noisy Sensor Data. ICDM Workshops 2018: 120-127 - 2017
- Kun Chen, Yu Liang, Zengliang Gao, Yi Liu:
Just-in-Time Correntropy Soft Sensor with Noisy Data for Industrial Silicon Content Prediction. Sensors 17(8): 1830 (2017) - Chao Huang, Dong Wang, Shenglong Zhu:
Where are you from: Home location profiling of crowd sensors from noisy and sparse crowdsourcing data. INFOCOM 2017: 1-9 - Chris Xiaoxuan Lu, Hongkai Wen, Sen Wang, Andrew Markham, Niki Trigoni:
SCAN: learning speaker identity from noisy sensor data. IPSN 2017: 67-78 - 2016
- Tatsuto Murayama, Peter Davis:
Noisy Data Aggregation with Independent Sensors: Insights and Open Problems. J. Multim. Inf. Syst. 3(2): 21-26 (2016)
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