How to Optimize Your CNN
July 14, 2016
Convolutional neural nets (CNNs) are not programmed in the traditional sense, but rather they are trained. The challenge to doing this is that you need a lot of good data which is already classified as the training material.
The process is not that different to some of the early training your brain got. Your parents probably had some picture books with pictures of cats, dogs, cows and so on, and would tell you what they were (and probably what noise they made but we’ll just focus on visual identification here).
To read the full article, click here
Related Semiconductor IP
- RVA23, Multi-cluster, Hypervisor and Android
- 64 bit RISC-V Multicore Processor with 2048-bit VLEN and AMM
- NPU IP Core for Mobile
- RISC-V AI Acceleration Platform - Scalable, standards-aligned soft chiplet IP
- H.264 Decoder
Related Blogs
- How to Augment SoC Development to Conquer Your Design Hurdles
- How to Secure Your Computing System's Power-Up Process with Secure Boot?
- How to Separate your Cryptographic Keys
- How to Shift Left on Low-Power Design Verification, Early and Quickly
Latest Blogs
- How fast a GPU do you need for your user interface?
- PCIe 6.x and 112 Gbps Ethernet: Synopsys and TeraSignal Achieve Optical Interconnect Breakthroughs
- Powering the Future of RF: Falcomm and GlobalFoundries at IMS 2025
- The Coming NPU Population Collapse
- Driving the Future of High-Speed Computing with PCIe 7.0 Innovation