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Muhammad Ali Chattha
Muhammad Ali Chattha
TU Kaiserslautern, DFKI
Geverifieerd e-mailadres voor dfki.de - Homepage
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FuseAD: Unsupervised anomaly detection in streaming sensors data by fusing statistical and deep learning models
M Munir, SA Siddiqui, MA Chattha, A Dengel, S Ahmed
Sensors 19 (11), 2451, 2019
982019
A comparative analysis of traditional and deep learning-based anomaly detection methods for streaming data
M Munir, MA Chattha, A Dengel, S Ahmed
2019 18th IEEE international conference on machine learning and applications …, 2019
462019
Kinn: Incorporating expert knowledge in neural networks
MA Chattha, SA Siddiqui, MI Malik, L van Elst, A Dengel, S Ahmed
arXiv preprint arXiv:1902.05653, 2019
142019
Pilot: A precise IMU based localization technique for smart phone users
MA Chattha, IH Naqvi
2016 IEEE 84th Vehicular Technology Conference (VTC-Fall), 1-5, 2016
102016
Deepex: Bridging the gap between knowledge and data driven techniques for time series forecasting
MA Chattha, SA Siddiqui, M Munir, MI Malik, L van Elst, A Dengel, ...
Artificial Neural Networks and Machine Learning–ICANN 2019: Deep Learning …, 2019
42019
A Survey on Knowledge integration techniques with Artificial Neural Networks for seq-2-seq/time series models
P Vadiraja, MA Chattha
arXiv preprint arXiv:2008.05972, 2020
22020
DeepLSF: Fusing Knowledge and Data for Time Series Forecasting
MA Chattha
Authorea Preprints, 2023
12023
KENN: enhancing deep neural networks by leveraging knowledge for time series forecasting
MA Chattha, L van Elst, MI Malik, A Dengel, S Ahmed
arXiv preprint arXiv:2202.03903, 2022
12022
Method and system for predicting trajectories for maneuver planning based on a neural network
S Zwicklbauer, MA Chattha, S Ahmed, VAN Ludger
US Patent App. 18/249,214, 2023
2023
Krnn: A Hybrid Data and Knowledge Oriented Time Series Forecasting Approach for Health Care Applications
MA Chattha, MI Malik, A Dengel, S Ahmed
Available at SSRN 4179221, 0
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Artikelen 1–10