ai for signals and images -凯发k8网页登录

wavelet techniques are effective for obtaining sparse, compressive data representations or features, which you can use in machine learning and deep learning workflows. wavelet toolbox™ supports deployment of multiscale feature extraction algorithms through matlab^® coder™ and gpu coder™ for a number of targets. to take advantage of the performance benefits offered by a modern graphics processing unit (gpu), certain wavelet toolbox functions can perform operations on a gpu. these functions provide gpu acceleration for your workflows. wavelet toolbox also provides functionality to perform signal labeling.