A Blog of the ZHAW Zurich University of Applied Sciences
Amin MazloumianHans-Joachim GelkeMatthias Rosenthal Institute of Embedded Systems Zurich University of Applied Sciences Zurich, Switzerland amin.mazloumian@zhaw.ch One third of food produced in the world for human consumption – approximately 1.3 billion tons – is lost or wasted every year. By classifying food waste of individual consumers and raising awareness of the measures, avoidable food waste […]
Using artificial intelligence algorithms, specifically neural networks on microcontrollers offers several possibilities but reveals challenges: limited memory, low computing power and no operating system. In addition, an efficient workflow to port neural networks algorithms to microcontrollers is required. Currently, several frameworks that can be used to port neural networks to microcontrollers are available. We evaluated […]
BY TOBIAS WELTI AND HANS-JOACHIM GELKE Due to their hardware architecture, Field Programmable Gate Arrays (FPGAs) are optimally suited for the execution of machine learning algorithms. These algorithms require the calculation of millions or even billions of multiplications for each input. To successfully accelerate a neural network, parallel execution of multiplication is the key. The […]
A computer with a GPU combined with an FPGA is a powerful tool for high speed video processing. An FPGA can preprocess multiple video streams in realtime and then send the data to the GPU for further processing. FPD-Link III is a cost-effective solution for high speed video transmission. It has made a name for […]
By Philipp Huber, Hans-Joachim Gelke, Matthias Rosenthal GPUs with their immense parallelization are best fitted for real-time video and signal processing. However, in a real-time system, the direct high-speed interface to the signal sources, such as cameras or sensors, is often missing. For this task, field programmable gate arrays (FPGA) are ideal for capturing and […]
IntEdgPerf is a new benchmark for running machine learning algorithms on embedded devices. It was developed at the Institute of Embedded Systems (InES) at the Zürich University of Applied Sciences. IntEdgPerf is a framework that allows a fair comparison between different embedded processors that can be used for executing neural networks. The area of embedded […]
We have developed a simple software to show how a custom keras model can be automatically translated into c-code. The generated c-code can, in combination with the ARM-CMSIS-NN functions, be used to run neural-net calculations in an efficient way on an embedded micro-controller such as the CORTEX-M4. The example software on GitHub has also firmware which runs on the […]
The HDMI2CSI board for capturing 4K HDMI was ported to the latest release of L4T (28.2.1) including the bug fix in the Nvidia VI (see forum: [1], [2]). Major differences where adapted from L4T 28.1 to L4T 28.2.1 and our developed hardware is again able to capture 2160p30. Run the tc358840 outside its specification (>1Gbps) […]
The NVIDA Tegra™ Processors TX1/TX2 with their powerful GPUs are ideal for use in professional audio mixing consoles or audio video equipment. However, if multiple audio channels are required, the TX1/TX2 is limited to I2S audio inputs. Utilizing the MIPI® Camera Serial Interface (CSI-2) and the InES I2S to CSI-2 converter IP, enables streaming of […]
Embedded devices like the Nvidia Tegra X1/2 offer tremendous video processing capabilities. But often there are bottlenecks hindering you from taking advantage of their full potential. One solution to this problem is to employ the general purpose compute capabilities of the GPU (GPGPU). For this purpose, we have developed a GStreamer Plug-In that lets you […]