Hierarchical Neural Networks
The German Traffic Sign Benchmark actually has the signs divided into groups: speed limits, danger signs, and so on. It turns out that humans make far fewer errors between groups than within groups. They might mistake a 30kph speed limit sign for an 80kph sign, but very rarely for a stop sign. The errors CNNs make are much less structured and are pretty much all over the place, so there is clearly room for improvement. How can we teach CNNs to be more like humans?
To read the full article, click here
Related Blogs
- Embedded Vision: The Road Ahead for Neural Networks and Five Likely Surprises
- Push-button generation of deep neural networks
- Deployable Artificial Neural Networks Will Change Everything
- Neural Networks and the Future
Latest Blogs
- Post-quantum security in platform management: PQShield is ready for SPDM 1.4
- Unleash Real-Time LiDAR Intelligence with Akida On-Chip AI
- Ceva Advancing Real-Time AI with Transformers and Intelligent Quantization
- X100 - Securing the System - RISC-V AI at the Edge
- Why Anti-tamper Sensors Matter: Agile Analog and Rambus Deliver Comprehensive Security Solution