This course will review the foundations of Deep Learning applied to vision including contemporary
convolutional network architectures.
Not exact matches
The second key technology, CNNP, achieved incredibly low power consumption by optimizing a
convolutional neural
network (CNN) in the areas of circuitry,
architecture, and algorithms.
«Deep
convolutional neural
networks (DCNNs) use a
network architecture similar to standard
convolutional neural
networks, but consist of a larger number of layers, which enables them to model more complicated functions.
Google's blog post says with the DeepLab - v3 + open source release also includes «models built on top of a powerful
convolutional neural
network (CNN) backbone
architecture for the most accurate results...» The post also points out that these systems of image segmentation have improved drastically over the last couple of years with advance in methods, hardware and datasets.