FPGAs take on convolutional neural networks
In the context of machine learning, a convolutional neural network (CNN, or ConvNet) can perhaps best be defined as a category of feed-forward artificial neural network in which the connectivity pattern between its neurons is inspired by the organization of the animal visual cortex. According to Stanford staff, convolutional Neural Networks are quite similar to ordinary neural networks, as they are comprised of neurons that have learnable weights and biases.
To read the full article, click here
Related Semiconductor IP
Related Blogs
- Embedded Vision: The Road Ahead for Neural Networks and Five Likely Surprises
- Push-button generation of deep neural networks
- Hierarchical Neural Networks
- Deployable Artificial Neural Networks Will Change Everything
Latest Blogs
- Cadence Unveils the Industry’s First eUSB2V2 IP Solutions
- Half of the Compute Shipped to Top Hyperscalers in 2025 will be Arm-based
- Industry's First Verification IP for Display Port Automotive Extensions (DP AE)
- IMG DXT GPU: A Game-Changer for Gaming Smartphones
- Rivos and Canonical partner to deliver scalable RISC-V solutions in Data Centers and enable an enterprise-grade Ubuntu experience across Rivos platforms