Discriminative locally linear mapping for medical diagnosis
Sign Up to like & getrecommendations! Published in 2019 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-018-7064-4
Abstract: Medical diagnosis based on machine learning has received growing interest in recent years. However, traditional classification algorithms often fail to appropriately deal with medical datasets because of their high dimensionality. Manifold learning is a branch… read more here.
Keywords: discriminative locally; linear mapping; medical diagnosis; mapping medical ... See more keywords
Model-based prediction of spatial gene expression via generative linear mapping
Sign Up to like & getrecommendations! Published in 2021 at "Nature Communications"
DOI: 10.1038/s41467-021-24014-x
Abstract: Decoding spatial transcriptomes from single-cell RNA sequencing (scRNA-seq) data has become a fundamental technique for understanding multicellular systems; however, existing computational methods lack both accuracy and biological interpretability due to their model-free frameworks. Here, we… read more here.
Keywords: scrna seq; model based; generative linear; linear mapping ... See more keywords
Cost-Efficient Super-Resolution Hardware Using Local Binary Pattern Classification and Linear Mapping for Real-Time 4K Conversion
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3036828
Abstract: We propose a new hardware-friendly super-resolution (SR) algorithm using computationally simple feature extraction and regression methods, i.e., local binary pattern (LBP) and linear mapping, respectively. The proposed method pre-trains dedicated linear mapping kernels for different… read more here.
Keywords: super resolution; hardware; local binary; linear mapping ... See more keywords