Muhammad Asad - Publications
Affiliations: | City, University of London |
Area:
machine learning, deep learning, pose, regressionYear | Citation | Score | |||
---|---|---|---|---|---|
2020 | Riaz A, Asad M, Alonso E, Slabaugh G. DeepFMRI: End-to-end deep learning for functional connectivity and classification of ADHD using fMRI. Journal of Neuroscience Methods. 335: 108506. PMID 32001294 DOI: 10.1016/J.Jneumeth.2019.108506 | 0.516 | |||
2018 | Riaz A, Asad M, Alonso E, Slabaugh G. Fusion of fMRI and non-imaging data for ADHD classification. Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society. 65: 115-128. PMID 29137838 DOI: 10.1016/j.compmedimag.2017.10.002 | 0.373 | |||
2017 | Olliverre N, Asad M, Yang G, Howe FA, Slabaugh GG. Pairwise mixture model for unmixing partial volume effect in multi-voxel MR spectroscopy of brain tumour patients Proceedings of Spie. 10134. DOI: 10.1117/12.2255026 | 0.518 | |||
2017 | Arif SMMRA, Asad M, Gundry M, Knapp K, Slabaugh G. Patch-based corner detection for cervical vertebrae in X-ray images Signal Processing-Image Communication. 59: 27-36. DOI: 10.1016/J.Image.2017.04.002 | 0.352 | |||
2017 | Asad M, Slabaugh GG. SPORE: Staged Probabilistic Regression for Hand Orientation Inference Computer Vision and Image Understanding. 161: 114-129. DOI: 10.1016/J.Cviu.2017.05.009 | 0.523 | |||
Show low-probability matches. |