This paper proposes a Design Space Exploration for Edge machine learning through the
utilization of the novel MathWorks FPGA Deep Learning Processor IP, featured in the HDL …

Security of inference phase deployment of Convolutional neural network (CNN) into
resource constrained embedded systems (eg low end FPGAs) is a growing research area …

In modern times, domain-specific accelerators require numerous functional components to
execute complex applications in a particular domain. To ensure efficient development, the …

Due to transistor shrinking, intermittent faults are a major concern in current digital systems.
This work presents an adaptive fault tolerance mechanism based on error correction codes …

Hardware accelerator-based CNN inference improves the performance and latency but
increases the time-to-market. As a result, CNN deployment on hardware is often outsourced …

Abstract Convolutional Neural Networks (CNNs) have applications in many valuable
domains such as object detection for autonomous cars and security using facial recognition …

This paper designs an optimized hardware generator (IP Generator) based on convolutional
neural networks. Users can use IP Generator to create any hardware architectures for neural …

Abstract Convolutional Neural Networks (CNNs) have become a widely popular method for
performing common computer vision tasks, such as image classification and object …