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A convolutional neural network (CNN) is a regularized type of feed-forward neural network that learns features by itself via filter (or kernel) optimization. This type of deep learning network has been applied to process and make predictions from many different types of data including text, images and audio. [1]
Region-based Convolutional Neural Networks (R-CNN) are a family of machine learning models for computer vision, and specifically object detection and localization. [1] The original goal of R-CNN was to take an input image and produce a set of bounding boxes as output, where each bounding box contains an object and also the category (e.g. car or ...
A deep CNN of (Dan Cireșan et al., 2011) at IDSIA was 60 times faster than an equivalent CPU implementation. [12] Between May 15, 2011, and September 10, 2012, their CNN won four image competitions and achieved SOTA for multiple image databases. [13] [14] [15] According to the AlexNet paper, [1] Cireșan's earlier net is "somewhat similar."
W3Schools [ae] Free Yes Yes Yes No No jQuery, tutorials WebFiddle [af] Free No Yes Yes No No JSFeed [ag] Free & Paid Yes Yes Yes Yes Yes HAML, Markdown, Jade, Less, Sass, Stylus, CoffeeScript, LiveScript, TypeScript, Babel LiveGap Editor [ah] Free Yes Yes Yes No No Less: ScratchPad [ai] Free Yes Yes No Yes No Runnable [aj] Free Yes Yes Yes No No
Caffe supports many different types of deep learning architectures geared towards image classification and image segmentation. It supports CNN, RCNN, LSTM and fully-connected neural network designs. [8] Caffe supports GPU- and CPU-based acceleration computational kernel libraries such as Nvidia cuDNN and Intel MKL. [9] [10]
In 1991, a CNN was applied to medical image object segmentation [55] and breast cancer detection in mammograms. [56] LeNet-5 (1998), a 7-level CNN by Yann LeCun et al., that classifies digits, was applied by several banks to recognize hand-written numbers on checks digitized in 32×32 pixel images. [57]
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
MATLAB + Deep Learning Toolbox (formally Neural Network Toolbox) MathWorks: 1992 Proprietary: No Linux, macOS, Windows: C, C++, Java, MATLAB: MATLAB: No No Train with Parallel Computing Toolbox and generate CUDA code with GPU Coder [23] No Yes [24] Yes [25] [26] Yes [25] Yes [25] Yes With Parallel Computing Toolbox [27] Yes Microsoft Cognitive ...