Focal-plane Sensor-processors (FPSPs) are a camera technology that enables low power, high frame rate computation, making the device suitable for edge computation. Unfortunately, the device’s limited instruction set and registers make the development of complex algorithms challenging. In this work, we present Cain – a compiler that targets SCAMP-5, a general-purpose FPSP – which generates SCAMP-5 code from multiple convolutional kernels. As an example, given the convolutional kernels for an MNIST digit recognition neural network, Cain produces code that is half as long, when compared to the other available compilers for SCAMP-5
The edge processing in ultra-low power IoT devices is increasing with the highest level of accuracy,...
Demand for computing is growing, especially in the form of digital image processing and computer vis...
Convolutional neural networks (CNNs) have achieved great success in image processing. However, the h...
Focal-plane Sensor-processors (FPSPs) are a camera technology that enables low power, high frame rat...
Focal-plane Sensor-Processor Arrays (FPSPs) are new imaging devices with parallel Single Instruction...
Convolutional Neural Networks impressed the world in 2012 by reaching state-of-the-art accuracy leve...
General-purpose processors, while tremendously versatile, pay a huge cost for their flexibility by w...
Thesis (Master's)--University of Washington, 2018Deep learning continues to be the revolutionary met...
Convolutional Networks (ConvNets) are biologically-inspired hierarchical architectures that can be t...
Convolutional Networks (ConvNets) are biologically-inspired hierarchical architectures that can be t...
International audience3D-integrated focal-plane array image processor chips offer new opportunities ...
International audience3D-integrated focal-plane array image processor chips offer new opportunities ...
International audience3D-integrated focal-plane array image processor chips offer new opportunities ...
Spiking convolutional neural networks have become a novel approach for machine vision tasks, due to...
The implementation of Texture Analysis algorithms on embedded devices requires reducing the computat...
The edge processing in ultra-low power IoT devices is increasing with the highest level of accuracy,...
Demand for computing is growing, especially in the form of digital image processing and computer vis...
Convolutional neural networks (CNNs) have achieved great success in image processing. However, the h...
Focal-plane Sensor-processors (FPSPs) are a camera technology that enables low power, high frame rat...
Focal-plane Sensor-Processor Arrays (FPSPs) are new imaging devices with parallel Single Instruction...
Convolutional Neural Networks impressed the world in 2012 by reaching state-of-the-art accuracy leve...
General-purpose processors, while tremendously versatile, pay a huge cost for their flexibility by w...
Thesis (Master's)--University of Washington, 2018Deep learning continues to be the revolutionary met...
Convolutional Networks (ConvNets) are biologically-inspired hierarchical architectures that can be t...
Convolutional Networks (ConvNets) are biologically-inspired hierarchical architectures that can be t...
International audience3D-integrated focal-plane array image processor chips offer new opportunities ...
International audience3D-integrated focal-plane array image processor chips offer new opportunities ...
International audience3D-integrated focal-plane array image processor chips offer new opportunities ...
Spiking convolutional neural networks have become a novel approach for machine vision tasks, due to...
The implementation of Texture Analysis algorithms on embedded devices requires reducing the computat...
The edge processing in ultra-low power IoT devices is increasing with the highest level of accuracy,...
Demand for computing is growing, especially in the form of digital image processing and computer vis...
Convolutional neural networks (CNNs) have achieved great success in image processing. However, the h...