Drosophila melanogasterDrosophila melanogaster is a species of fly (the taxonomic order Diptera) in the family Drosophilidae. The species is often referred to as the fruit fly or lesser fruit fly, or less commonly the "vinegar fly" or "pomace fly". Starting with Charles W. Woodworth's 1901 proposal of the use of this species as a model organism, D. melanogaster continues to be widely used for biological research in genetics, physiology, microbial pathogenesis, and life history evolution.
Caenorhabditis elegansCaenorhabditis elegans (ˌsiːnoʊræbˈdaɪtəs_ˈɛləɡæns) is a free-living transparent nematode about 1 mm in length that lives in temperate soil environments. It is the type species of its genus. The name is a blend of the Greek caeno- (recent), rhabditis (rod-like) and Latin elegans (elegant). In 1900, Maupas initially named it Rhabditides elegans. Osche placed it in the subgenus Caenorhabditis in 1952, and in 1955, Dougherty raised Caenorhabditis to the status of genus. C.
Shrinkage (statistics)In statistics, shrinkage is the reduction in the effects of sampling variation. In regression analysis, a fitted relationship appears to perform less well on a new data set than on the data set used for fitting. In particular the value of the coefficient of determination 'shrinks'. This idea is complementary to overfitting and, separately, to the standard adjustment made in the coefficient of determination to compensate for the subjunctive effects of further sampling, like controlling for the potential of new explanatory terms improving the model by chance: that is, the adjustment formula itself provides "shrinkage.
Maximum likelihood estimationIn statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data. This is achieved by maximizing a likelihood function so that, under the assumed statistical model, the observed data is most probable. The point in the parameter space that maximizes the likelihood function is called the maximum likelihood estimate. The logic of maximum likelihood is both intuitive and flexible, and as such the method has become a dominant means of statistical inference.
Automatic image annotationAutomatic image annotation (also known as automatic image tagging or linguistic indexing) is the process by which a computer system automatically assigns metadata in the form of captioning or keywords to a . This application of computer vision techniques is used in systems to organize and locate images of interest from a database. This method can be regarded as a type of multi-class with a very large number of classes - as large as the vocabulary size.
Model organismA model organism (often shortened to model) is a non-human species that is extensively studied to understand particular biological phenomena, with the expectation that discoveries made in the model organism will provide insight into the workings of other organisms. Model organisms are widely used to research human disease when human experimentation would be unfeasible or unethical. This strategy is made possible by the common descent of all living organisms, and the conservation of metabolic and developmental pathways and genetic material over the course of evolution.
Pose (computer vision)In the fields of computing and computer vision, pose (or spatial pose) represents the position and orientation of an object, usually in three dimensions. Poses are often stored internally as transformation matrices. The term “pose” is largely synonymous with the term “transform”, but a transform may often include scale, whereas pose does not. In computer vision, the pose of an object is often estimated from camera input by the process of pose estimation.
Caenorhabditis briggsaeCaenorhabditis briggsae is a small nematode, closely related to Caenorhabditis elegans. The differences between the two species are subtle. The male tail in C. briggsae has a slightly different morphology from C. elegans. Other differences include changes in vulval precursor competence and the placement of the excretory duct opening. C. briggsae is frequently used to study the differences between it and the more intimately understood C. elegans, especially at the DNA and protein sequence level.
Training, validation, and test data setsIn machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms function by making data-driven predictions or decisions, through building a mathematical model from input data. These input data used to build the model are usually divided into multiple data sets. In particular, three data sets are commonly used in different stages of the creation of the model: training, validation, and test sets.
Facial recognition systemA facial recognition system is a technology potentially capable of matching a human face from a or a video frame against a database of faces. Such a system is typically employed to authenticate users through ID verification services, and works by pinpointing and measuring facial features from a given image. Development began on similar systems in the 1960s, beginning as a form of computer application. Since their inception, facial recognition systems have seen wider uses in recent times on smartphones and in other forms of technology, such as robotics.
