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
- Cadence Extends Support for Automotive Solutions on Arm Zena Compute Subsystems
- The Role of GPU in AI: Tech Impact & Imagination Technologies
- Time-of-Flight Decoding with Tensilica Vision DSPs - AI's Role in ToF Decoding
- Synopsys Expands Collaboration with Arm to Accelerate the Automotive Industry’s Transformation to Software-Defined Vehicles
- Deep Robotics and Arm Power the Future of Autonomous Mobility