Add to ORKGThe winners, as well as the organizers and sponsors of the IEEE Low-Power Computer Vision Challenge, share their insights into making computer vision (CV) more efficient for running on mobile or embedded systems. As CV (and more generally, artificial intelligence) is deployed widely on the Internet of Things, efficiency will become increasingly important
Computing has undergone a significant transformation over the past two decades, shifting from a mach...
Mobile vision is enabling many new applications such as face recognition and augmented reality. Howe...
AI processor, which can run artificial intelligence algorithms, is a state-of-the-art accelerator,in...
The winners, as well as the organizers and sponsors of the IEEE Low-Power Computer Vision Challenge,...
Energy efficiency is critical for running computer vision on battery-powered systems, such as mobile...
Computer vision has achieved impressive progress in recent years. Meanwhile, mobile phones have beco...
The rapid rise of artificial-intelligence (AI) applications on big data such as image collection, ha...
Despite strong interest in embedded computer vision, the computational demands of Convolutional Neur...
The Low-Power Image Recognition Challenge (LPIRC, this https URL) is an annual competition started i...
Over the past two decades, the use of low power Field Programmable Gate Arrays (FPGA) for the accele...
Technology scaling has driven computing devices to be faster, cheaper, and smaller while consuming l...
Modern-day life is driven by electronic devices connected to the internet. The emerging research fie...
International audienceWe present the results of recent challenges in Automated Computer Vision (Auto...
Over the past two decades, the use of low power Field Programmable Gate Arrays (FPGA) for the accele...
This article describes the novel Tree-based Unidirectional Neural Network (TRUNK) architecture. This...
Computing has undergone a significant transformation over the past two decades, shifting from a mach...
Mobile vision is enabling many new applications such as face recognition and augmented reality. Howe...
AI processor, which can run artificial intelligence algorithms, is a state-of-the-art accelerator,in...
The winners, as well as the organizers and sponsors of the IEEE Low-Power Computer Vision Challenge,...
Energy efficiency is critical for running computer vision on battery-powered systems, such as mobile...
Computer vision has achieved impressive progress in recent years. Meanwhile, mobile phones have beco...
The rapid rise of artificial-intelligence (AI) applications on big data such as image collection, ha...
Despite strong interest in embedded computer vision, the computational demands of Convolutional Neur...
The Low-Power Image Recognition Challenge (LPIRC, this https URL) is an annual competition started i...
Over the past two decades, the use of low power Field Programmable Gate Arrays (FPGA) for the accele...
Technology scaling has driven computing devices to be faster, cheaper, and smaller while consuming l...
Modern-day life is driven by electronic devices connected to the internet. The emerging research fie...
International audienceWe present the results of recent challenges in Automated Computer Vision (Auto...
Over the past two decades, the use of low power Field Programmable Gate Arrays (FPGA) for the accele...
This article describes the novel Tree-based Unidirectional Neural Network (TRUNK) architecture. This...
Computing has undergone a significant transformation over the past two decades, shifting from a mach...
Mobile vision is enabling many new applications such as face recognition and augmented reality. Howe...
AI processor, which can run artificial intelligence algorithms, is a state-of-the-art accelerator,in...