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Most recent deep learning based methods have demonstrated superior performance over the previous hand-crafted methods.
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Culture-based methods have demonstrated a defect in the intracellular killing of Staphylococcus aureus [ 69, 75, 76], Streptococcus pneumoniae [ 71, 77] and Candida albicans [ 78].
Among them, machine learning-based methods have demonstrated their advantage and showed better performance than the other two categories of methods when a large annotated corpus is available.
However for the past decade, most studies on normal vaginal flora with PCR-based methods have demonstrated the presence and dominance of L. crispatus, L. gasseri and/or L. jensenii.
Wavelet based data compression methods have demonstrated superior performance over the conventional interpolative methods.
Both methods have demonstrated efficiency in increasing osseointegration levels.
Based on experimental testing of real and simulated data sets, the HRHF method has demonstrated its effectiveness in protecting location privacy and efficiency in providing quality services.
The proposed method has demonstrated its ability to handle pose variations problems and can be used for both image and video based facial expression recognition.
SIFT method has demonstrated very good qualities to represent images.
Face-detection methods based on cascade architecture have demonstrated a fast and robust performance.
Multiple alignment methods based on probabilistic consistency have demonstrated great promise in the context of amino-acid alignment [75] and aligning collinear genomic regions [33], and in principle, could be extended to genome alignment with rearrangement.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com