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  2. CellCognition - Wikipedia

    en.wikipedia.org/wiki/CellCognition

    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.

  3. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    3-dimensional pen tip velocity trajectory matrix for each sample 2858 Text Handwriting recognition, classification 2008 [134] [135] B. Williams Chars74K Dataset Character recognition in natural images of symbols used in both English and Kannada: 74,107 Character recognition, handwriting recognition, OCR, classification 2009 [136] T. de Campos

  4. Cell–cell recognition - Wikipedia

    en.wikipedia.org/wiki/Cellcell_recognition

    These events can be grouped into two main categories: Intrinsic Recognition and Extrinsic Recognition. [3] Intrinsic Recognition is when cells that are part of the same organism associate. [3] 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 ...

  5. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Provides classification and regression datasets in a standardized format that are accessible through a Python API. Metatext NLP: https://metatext.io/datasets web repository maintained by community, containing nearly 1000 benchmark datasets, and counting.

  6. Project Euler - Wikipedia

    en.wikipedia.org/wiki/Project_Euler

    The first Project Euler problem is Multiples of 3 and 5. If we list all the natural numbers below 10 that are multiples of 3 or 5, we get 3, 5, 6 and 9. The sum of these multiples is 23. Find the sum of all the multiples of 3 or 5 below 1000. It is a 5% rated problem, indicating it is one of the easiest on the site.

  7. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    Recurrent neural networks (RNNs) are a class of artificial neural network commonly used for sequential data processing. Unlike feedforward neural networks, which process data in a single pass, RNNs process data across multiple time steps, making them well-adapted for modelling and processing text, speech, and time series.

  8. Zero-shot learning - Wikipedia

    en.wikipedia.org/wiki/Zero-shot_learning

    The name is a play on words based on the earlier concept of one-shot learning, in which classification can be learned from only one, or a few, examples. Zero-shot methods generally work by associating observed and non-observed classes through some form of auxiliary information, which encodes observable distinguishing properties of objects. [ 1 ]

  9. Glossary of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Glossary_of_artificial...

    Pronounced "A-star". A graph traversal and pathfinding algorithm which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. abductive logic programming (ALP) A high-level knowledge-representation framework that can be used to solve problems declaratively based on abductive reasoning. It extends normal logic programming by allowing some ...