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A residual neural network (also referred to as a residual network or ResNet) [1] is a deep learning architecture in which the layers learn residual functions with reference to the layer inputs. It was developed in 2015 for image recognition , and won the ImageNet Large Scale Visual Recognition Challenge ( ILSVRC ) of that year.
Gated recurrent units (GRUs) are a gating mechanism in recurrent neural networks, introduced in 2014 by Kyunghyun Cho et al. [1] The GRU is like a long short-term memory (LSTM) with a gating mechanism to input or forget certain features, [2] but lacks a context vector or output gate, resulting in fewer parameters than LSTM. [3]
Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning.The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.
ResNet may refer to: Residential network, a computer network provided by a university to serve residence halls; Residual flow network, in graph theory;
U-Net is a convolutional neural network that was developed for image segmentation. [1] The network is based on a fully convolutional neural network [ 2 ] whose architecture was modified and extended to work with fewer training images and to yield more precise segmentation .
The ImageNet training set contained 1.2 million images. The model was trained for 90 epochs over a period of five to six days using two Nvidia GTX 580 GPUs (3GB each). [1] These GPUs have a theoretical performance of 1.581 TFLOPS in float32 and were priced at US$500 upon release. [3] Each forward pass of AlexNet required approximately 4 GFLOPs. [4]
FOSS stands for "Free and Open Source Software". There is no one universally agreed-upon definition of FOSS software and various groups maintain approved lists of licenses. The Open Source Initiative (OSI) is one such organization keeping a list of open-source licenses. [1] The Free Software Foundation (FSF) maintains a list of what it ...
The ImageNet project is a large visual database designed for use in visual object recognition software research. More than 14 million [1] [2] images have been hand-annotated by the project to indicate what objects are pictured and in at least one million of the images, bounding boxes are also provided. [3]