machine learning
http://www.yso.fi/onto/yso/p21846
Related people
Related publications and other outputs
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- 2023 Roadmap on molecular modelling of electrochemical energy materials (2023) Zhang, Chao; et al.; A1; OA
- A comparison of machine learning architectures for determining ground contact timings in overground and treadmill gait (2023) Sansgiri, Sailee; et al.; O1
- Additive autoencoder for dimension estimation (2023) Kärkkäinen, Tommi; et al.; A1; OA
- A deep learning model developed for sleep apnea detection : A multi-center study (2023) Li, Fan; et al.; A1
- Advancing nanomaterials design using novel machine learning methods (2023) Linja, Joakim; G5; OA; 978-951-39-9517-1
- An efficient memory reserving-and-fading strategy for vector quantization based 3D brain segmentation and tumor extraction using an unsupervised deep learning network (2023) De, Ailing; et al.; A1
- Annotation-efficient training of medical image segmentation network based on scribble guidance in difficult areas (2023) Zhuang, Mingrui; et al.; A1
- Applications of Artificial Intelligence in the Economy, Including Applications in Stock Trading, Market Analysis, and Risk Management (2023) Rahmani, Amir Masoud; et al.; A2; OA
- Applying machine learning methods for the analysis of two-dimensional mass spectra (2023) Gao, Z.; et al.; A1; OA
- A Successful Crowdsourcing Approach for Bird Sound Classification (2023) Lehikoinen, Petteri; et al.; A1; OA
Related research datasets
- Assessment of microalgae species, biomass and distribution from spectral images using a convolution neural network (2021) Salmi, Pauliina; et al.
- Au38Q MBTR-K3 (2020) Linja, Joakim; et al.; doi:10.5281/zenodo.4268064
- Kernels and Graphs on M25 + H (2023) Pihlajamäki, Antti; et al.
- Kernels and Graphs on M25 + H (parent repository) (2023) Pihlajamäki, Antti; et al.
- Supplementary data for the article "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions" (2022) Hyttinen, Noora
