Search results
Results From The WOW.Com Content Network
A wide variety of measurements can be generated for each identified cell or subcellular compartment, including morphology, intensity, and texture among others. These measurements are accessible by using built-in viewing and plotting data tools, exporting in a comma-delimited spreadsheet format, [ 9 ] or importing into a MySQL or SQLite database.
CellCognition uses a computational pipeline which includes image segmentation, object detection, feature extraction, statistical classification, tracking of individual cells over time, detection of class-transition motifs (e.g. cells entering mitosis), and HMM correction of classification errors on class labels.
Extrinsic Recognition is when the cell of one organism recognizes a cell from another organism, like when a mammalian cell detects a microorganism in the body. [3] The molecules that complete this binding consist of proteins, carbohydrates, and lipids, resulting in a variety of glycoproteins , lipoproteins , and glycolipoproteins. [ 3 ]
Whether both types of stellate cells have the same function is not clear, as layer I has excitatory spiny cells and layer II has inhibitory aspiny cells. The latter indicates a much different network. At line 10, the squash function can be replaced by other functions and network topologies that retain the vector direction.
Brainoware computer can identify people by their voice
BGSLibrary includes the original LBP implementation for motion detection [12] as well as a new LBP operator variant combined with Markov Random Fields [13] with improved recognition rates and robustness. dlib, an open source C++ library: implementation. scikit-image, an open source Python library. Provides a c-based python implementation for LBP
[6] [7] [8] Each input sample is a graph representation of a molecule, where atoms form the nodes and chemical bonds between atoms form the edges. In addition to the graph representation, the input also includes known chemical properties for each of the atoms.
A cellular automaton consists of a regular grid of cells, each in one of a finite number of states, such as on and off (in contrast to a coupled map lattice). The grid can be in any finite number of dimensions. For each cell, a set of cells called its neighborhood is defined relative to the specified cell.