Ren, Huamin, Olsen, Rasmus Løvenstein & Schwefel, Hans-Peter (2024). How Much Measurement Data is Required for Day-ahead Load Forecasting while using Sequential Models? I SmartGridComm 2024, . (red.) 2024 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids-SmartGridComm. IEEE (Institute of Electrical and Electronics Engineers). ISBN 979-8-3503-1855-5. s 378-384. doi:
Jensen, Markus Wiik, Ren, Huamin & Shalaginov, Andrii (2024). Day-ahead Forecasting Electricity Spot Prices in Norway with ARIMA, XGBoost and LSTM Models. International Journal On Advances in Systems and Measurements. ISSN 1942-261X. 17(3&4) s 127-137.
Jensen, Markus Wiik, Ren, Huamin & Shalaginov, Andrii (2024). Day-ahead Electricity Price Forecasting of Elspot Markets in Norway. ENERGY, International Conference on Smart Grids, Green Communications and IT Energy-aware Technologies. ISSN 2308-412X. (1)
Ren, Huamin, Liu, Yajie & Paudel, Keshav Prasad (2023). Cod Catch Forecasting through Machine Learning Algorithms at the Haul Level. I Sehring, Hans-Werner, Chan, Steven, Caicedo-Castro, Isaac, Zhukov, Arcady & Sterritt, Roy (red.) IARIA Congress 2023 : The 2023 IARIA Annual Congress on Frontiers in Science, Technology, Services, and Applications. International Academy, Research and Industry Association (IARIA). ISBN 978-1-68558-089-6. s 123-128.
Ren, Huamin, Su, Xiaomeng, Jenssen, Robert, Li, Jingyue & Anfinsen, Stian Normann (2022). Attention-guided Temporal Convolutional Network for Non-intrusive Load Monitoring. I IEEE SmartGridComm 2022, . (red.) 2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids - SmartGridComm. IEEE (Institute of Electrical and Electronics Engineers). ISBN 978-1-6654-3254-2. s 419-425. doi:
Ren, Huamin, Bianchi, Filippo Maria, Li, Jingyue, Olsen, Rasmus L., Jenssen, Robert & Anfinsen, Stian Normann (2021). Towards Applicability: A Comparative Study on Non-Intrusive Load Monitoring Algorithms. I Pack, Sangheon (red.) Proceeding of the 2021 IEEE International Conference on Consumer Electronics (ICCE). IEEE conference proceedings. ISBN 978-1-7281-9766-1. doi:
Ren, Huamin, Nattiya, Kanhabua, Møgelmose, Andreas, Liu, Weifeng, Kulkarni, Kaustubh, Escalera, Sergio, Baro, Xavier & Moeslund, Thomas B. (2018). Back-Dropout Transfer Learning for Action Recognition. IET Computer Vision. ISSN 1751-9632. 12 (4) s 484-491.
Ren, Huamin, Pan, Hong, Olsen, Søren Ingvor, Jensen, Morten Bornø & Moeslund, Thomas B. (2016). An in-depth study of sparse codes on abnormality detection. IEEE conference proceedings. ISBN 978-1-5090-3811-4.
Ren, Huamin, Liu, Weifeng, Olsen, Søren Ingvor, Escalera, Sergio & Moeslund, Thomas B. (2015). Unsupervised behavior-specific dictionary learning for abnormal event detection. The British Machine Vision Association (BMVA) Press. ISBN 978-1-901725-36-0.
Ren, Huamin & Moeslund, Thomas B. (2014). Abnormal event detection using local sparse representation. IEEE Computer Society Digital Library. ISBN 978-1-4799-4871-0.
Ren, Huamin & Moeslund, Thomas B. (2014). Action recognition using salient neighboring histograms. IEEE Computer Society Digital Library. ISBN 978-1-4799-2341-0.
Ren, Huamin, Moeslund, Thomas B. & Ramampiaro, Heri (2013). Small Vocabulary with Saliency Matching for Video Copy Detection. SciTePress. ISBN 978-989-8565-48-8.
Have, Simon Hartmann, Ren, Huamin & Moeslund, Thomas (2013). Real-time Multiple Abnormality Detection in Video Data. SciTePress. ISBN 978-989-8565-48-8.
Ren, Huamin, Ramampiaro, Heri, Zhang, Yongdong & Lin, Shouxun (2012). An incremental clustering based codebook construction in video copy detection. IEEE Computer Society Digital Library. ISBN 978-1-4673-1830-3.
