… have been developed to aid in phenotypic classification and clustering of data acquired from
… computer vision and machine-learning methods for generating and categorizing phenotypic …

… These algorithms can be trained to recognize subtle differences in the phenotypic profile
space to either explore novel phenotypes or learn to distinguish known phenotypes with …

… these perturbations and cellular phenotypes. In functional genomics … In the following sections
we review the computer vision … (C) Clustering and profiling: unsupervised machine learning …

… This limitation in selecting for root phenotypes in soybean and other pulse, oilseed and
cereal … root shape profiles enabling the user to select which profile was most appropriate [107]. …

… extol computer vision (CV; for a definition of terms in italics see see Box 1), the automatic
extraction of meaningful information from images, as a promising toolbox to collect phenotypic …

… recognition, profiling, and prediction of visual phenotypes to … Capturing the complexity and
subtlety of cellular phenotypes … deep learning–based computer vision methods has enabled …

… We present NeuriteTracker, a computer vision (CV) … phenotypic categories at the static
level, we used a mathematical model that selects specific cells with a highly penetrant phenotype …

… of deep learning techniques in computer vision, natural language … Morphological profiling
is a complementary approach that can be … provided by morphological profiling, it is sometimes …

… Most of the feature selection and mapping methods developed for high-dimensional data
in the data mining, computer vision, document classification, and bioinformatics fields are …

… Beyond deep-learning, computer vision could benefit bioimage analysis in many more
ways. However, those methods were originally addressed to computer vision experts and …