Seeing what's not there. IMG Series 4 NNA meets Visidon's deep-learning-based Super Resolution technology
Last year I read a fascinating article on LinkedIn about using deep-learning-based super-resolution networks to increase the apparent detail contained in images and videos sent back by Nasa’s Perseverance Rover. This article got me thinking about how, when I first watched Blade Runner in the 90s, scenes such as “enhance 15 to 23” seemed so implausible based on the technology available at that time. At that point (and because of films like Blade Runner) I was embarking on a three-year degree course in artificial intelligence and I could not have predicted the impact of the deep learning revolution at the start of the millennium. You can’t add what isn’t there, I kept saying to myself. But now, it seems, you can – and it’s extremely convincing.
Related Semiconductor IP
- JESD204D Transmitter and Receiver IP
- 100G UDP IP Stack
- Frequency Synthesizer
- Temperature Sensor IP
- LVDS Driver/Buffer
Related Blogs
- Imagination China sees 2020 out in award-winning style with IMG Series 4 NNA
- Efficient inference on IMG Series4 NNAs
- Intel vs. ARM: In the Smartphone Era (Part 4)
- Cortex-M Series - spectacular growth and progress
Latest Blogs
- Why Choose Hard IP for Embedded FPGA in Aerospace and Defense Applications
- Migrating the CPU IP Development from MIPS to RISC-V Instruction Set Architecture
- Quintauris: Accelerating RISC-V Innovation for next-gen Hardware
- Say Goodbye to Limits and Hello to Freedom of Scalability in the MIPS P8700
- Why is Hard IP a Better Solution for Embedded FPGA (eFPGA) Technology?