Embedded vision developers embrace neural networks

February 03, 2020 //By Peter Clarke
Embedded vision developers embrace neural networks
A survey conducted by the Edge AI and Vision Alliance shows a sharp jump in the use of neural networks for computer vision applications in 2019.

The percentage of active users of neural networks went up to 81 percent in 2019 from 59 percent in 2018. The percentage using or planning to use neural networks hit 94 percent.

The most popular platforms to run those neural networks on remain CPUs and GPUs although their use is diminishing in favour of dedicated computer vision processors and dedicated deep learning processors, the survey reveals.

The survey revealed that TensorFlow remains the most popular software framework for designing, training and evaluating neural networks for vision tasks. However, it's popularity is declining rapidly in favour of almost all other approaches including Caffe, Caffe2, Matlab and most notably in 2019 Mxnet.

The survey was conducted among 705 computer vision developers across a range of industries, organizations, geographical locations and job types in October 2019. The Edge AI and Vision Alliance used to be known as the Embedded Vision Alliance.

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