FPGAs take on convolutional neural networks
May 8, 2017
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
- A Comparison on Different AMBA 5 CHI Verification IPs
- Cadence Recognized as TSMC OIP Partner of the Year at 2025 OIP Ecosystem Forum
- Accelerating Development Cycles and Scalable, High-Performance On-Device AI with New Arm Lumex CSS Platform
- Desktop-Quality Ray-Traced Gaming and Intelligent AI Performance on Mobile with New Arm Mali G1-Ultra GPU
- Powering Scale Up and Scale Out with 224G SerDes for UALink and Ultra Ethernet