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Convolutional neural network (CNN), well-knownto be computationally intensive, is a fundamental algorithmicbuilding block in many computer vision and artificial intelligenceapplications that follow the deep learning principle. This workpresents a novel stochastic-based and scalable hardware architectureand circuit design that computes a convolutional neuralnetwork with FPGA. The key idea is to implement...
Convolutional Neural Networks (CNNs) are a variation of feed-forward Neural Networks inspired by the biological process in the visual cortex of animals. The interest in this supervised learning algorithm has rapidly grown in many fields like image and video recognition and natural language processing. Nowadays they have become the state of the art in various applications like mobile robot vision,...
Obstructive Sleep Apnea (OSA) is one of the main sleep disorders, but only 10% of the cases are diagnosed. Moreover, there is a lack of tools for long-term monitoring of OSA, since current systems are too bulky and intrusive to be used continuously. In this context, recent studies have shown that it is possible to detect it automatically based on single-lead ECG recordings. This approach can be used...
We present an integrated hardware/software architectureto enforce security in networked workstations andembedded devices such as printers and microscopes. Thesedevices are usually connected to the Internet without protection, so they are exposed to attack. Our solution operatesas an intermediate isolation and protection module (IPM) between the network and the device to be protected. TheIPM can be...
Convolutional Neural Network (CNN) has become a successful algorithm in the region of artificial intelligence and a strong candidate for many applications. However, for embedded platforms, CNN-based solutions are still too complex to be applied if only CPU is utilized for computation. Various dedicated hardware designs on FPGA and ASIC have been carried out to accelerate CNN, while few of them explore...
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