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  2. List of datasets in computer vision and image processing

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

    Multi-modal dataset for obstacle detection in agriculture including stereo camera, thermal camera, web camera, 360-degree camera, lidar, radar, and precise localization. Classes labelled geographically. >400 GB of data Images and 3D point clouds Classification, object detection, object localization 2017 [52] M. Kragh et al.

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

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

    On the Evaluation of Unsupervised Outlier Detection: Measures, Datasets, and an Empirical Study Most data files are adapted from UCI Machine Learning Repository data, some are collected from the literature. treated for missing values, numerical attributes only, different percentages of anomalies, labels 1000+ files ARFF: Anomaly detection

  4. Precision agriculture - Wikipedia

    en.wikipedia.org/wiki/Precision_agriculture

    Machine learning is commonly used in conjunction with drones, robots, and internet of things devices. It allows for the input of data from each of these sources. The computer then processes this information and sends the appropriate actions back to these devices.

  5. List of protein subcellular localization prediction tools

    en.wikipedia.org/wiki/List_of_protein_sub...

    Evolutionary support vector machine (ESVM) based classifier with automatic selection from a large set of physicochemical composition (PCC) features to design an accurate system for predicting protein subnuclear localization.

  6. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    Hugging Face, Inc. is a Franco-American company that develops computation tools for building applications using machine learning. It is known for its transformers library built for natural language processing applications.

  7. Perturb-seq - Wikipedia

    en.wikipedia.org/wiki/Perturb-seq

    Perturb-seq (also known as CRISP-seq and CROP-seq) refers to a high-throughput method of performing single cell RNA sequencing (scRNA-seq) on pooled genetic perturbation screens. [ 1 ] [ 2 ] [ 3 ] Perturb-seq combines multiplexed CRISPR mediated gene inactivations with single cell RNA sequencing to assess comprehensive gene expression ...

  8. Shogun (toolbox) - Wikipedia

    en.wikipedia.org/wiki/Shogun_(toolbox)

    Shogun is a free, open-source machine learning software library written in C++. It offers numerous algorithms and data structures for machine learning problems. It offers interfaces for Octave, Python, R, Java, Lua, Ruby and C# using SWIG. It is licensed under the terms of the GNU General Public License version 3 or later.

  9. Chi-square automatic interaction detection - Wikipedia

    en.wikipedia.org/wiki/Chi-square_automatic...

    Luchman, J.N.; CHAIDFOREST: Stata module to conduct random forest ensemble classification based on chi-square automated interaction detection (CHAID) as base learner, Available for free download, or type within Stata: ssc install chaidforest. IBM SPSS Decision Trees grows exhaustive CHAID trees as well as a few other types of trees such as CART.