Separable convolutions are an important technique for implementing efficient convolutional neural networks (CNNs), made popular by MobileNet’s use of depthwise separable convolutions. But separable convolutions are not a new concept, and their utility is not limited to CNNs. Separable convolutions […]
MediaTek has incorporated an AI processing unit (APU) alongside the traditional CPU and GPU in its SoC designs for the next wave of smart client devices (smartphones, cameras, appliances, cars, etc.). Edge applications can harness the CPU, GPU and APU […]
Drivers are the biggest source of uncertainty in the operation of cars. Computer vision is helping to eliminate human error and make the roads safer. But 14 years after autonomous vehicles successfully completed the DARPA Grand Challenge, the question remains: […]
Usually, the top places in deep learning challenges are won by huge neural networks that require massive amounts of data and computation, making them impractical for use in real-time edge applications like security and autonomous driving. In this talk we […]
Deep learning on embedded devices is currently enjoying significant success in a number of vision applications – particularly smartphones, where increasingly prevalent AI cameras are able to enhance every captured moment. However, the considerable number of deep learning network architectures […]
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