Image processing plays an important role in medical image analysis. The most popular methods for image processing and analysis are very resource hungry, which leads to some disadvantages in their applications even on a powerful desktop computers. On the other side, modern mobile devices are equipped with powerful processors with an efficient instruction architecture. This lead to better performance per watt than a desktop CPUs. This work investigates the performance of a widely used medical analysis algorithm implemented on a modern mobile devices and desktop CPU. The results obtained with ARM NEON instructions show speed improvements up to 2 times. As this research shows mobile devices cannot yet compete with powerful desktop CPUs, even wi...
Mobile vision is enabling many new applications such as face recognition and augmented reality. Howe...
The future multi-modal user interfaces of battery-powered mobile devices are expected to require com...
Abstract. There exist several algorithm setups to realize object recognition systems. But actually i...
Majority of current mobile devices include a camera. To meet the form-factor and price requirements,...
International audienceImage processing technology has grown significantly over the past decade. Its ...
Techniques of medical image processing and analysis play a crucial role in many clinical scenarios, ...
With the rapid advances in mobile technology many mobile devices are capable of capturing high quali...
Medical imaging has become an absolutely essential diagnostic tool for clinical practices; at presen...
Modern graphics processing units (GPUs) can provide tremendous performance boosts for some applicati...
Abstract—Noise reduction is one of the most fundamental digital image processing challenges. On mobi...
With the enormous growth in popularity of mobile devices in the past decade, there has been a large ...
This work presents a technique to optimize processing image algorithms. The increasing demand for vi...
This work explores the possibility of applying edge machine learning technology in the context of po...
The portability of Convolutional Neural Networks (ConvNets) on the mobile edge of the Internet has p...
Modern advancements in configurable hardware, most notably Field-Programmable Gate Arrays (FPGAs), h...
Mobile vision is enabling many new applications such as face recognition and augmented reality. Howe...
The future multi-modal user interfaces of battery-powered mobile devices are expected to require com...
Abstract. There exist several algorithm setups to realize object recognition systems. But actually i...
Majority of current mobile devices include a camera. To meet the form-factor and price requirements,...
International audienceImage processing technology has grown significantly over the past decade. Its ...
Techniques of medical image processing and analysis play a crucial role in many clinical scenarios, ...
With the rapid advances in mobile technology many mobile devices are capable of capturing high quali...
Medical imaging has become an absolutely essential diagnostic tool for clinical practices; at presen...
Modern graphics processing units (GPUs) can provide tremendous performance boosts for some applicati...
Abstract—Noise reduction is one of the most fundamental digital image processing challenges. On mobi...
With the enormous growth in popularity of mobile devices in the past decade, there has been a large ...
This work presents a technique to optimize processing image algorithms. The increasing demand for vi...
This work explores the possibility of applying edge machine learning technology in the context of po...
The portability of Convolutional Neural Networks (ConvNets) on the mobile edge of the Internet has p...
Modern advancements in configurable hardware, most notably Field-Programmable Gate Arrays (FPGAs), h...
Mobile vision is enabling many new applications such as face recognition and augmented reality. Howe...
The future multi-modal user interfaces of battery-powered mobile devices are expected to require com...
Abstract. There exist several algorithm setups to realize object recognition systems. But actually i...