Buscar
Mostrando ítems 1-10 de 30
Ponencia
Deep Spiking Neural Network model for time-variant signals classification: a real-time speech recognition approach
(IEEE Computer Society, 2018)
Speech recognition has become an important task to improve the human-machine interface. Taking into account the limitations of current automatic speech recognition systems, like non-real time cloud-based solutions or ...
Ponencia
Multi-dataset Training for Medical Image Segmentation as a Service
(ScitePress Digital Library, 2019)
Deep Learning tools are widely used for medical image segmentation. The results produced by these techniques depend to a great extent on the data sets used to train the used network. Nowadays many cloud service providers ...
Artículo
Performance Evaluation of Deep Learning-Based Prostate Cancer Screening Methods in Histopathological Images: Measuring the Impact of the Model’s Complexity on Its Processing Speed
(MDPI, 2021-01)
Prostate cancer (PCa) is the second most frequently diagnosed cancer among men worldwide, with almost 1.3 million new cases and 360,000 deaths in 2018. As it has been estimated, its mortality will double by 2040, mostly ...
Ponencia
Comprehensive Evaluation of OpenCL-Based CNN Implementations for FPGAs
(Springer, 2017)
Deep learning has significantly advanced the state of the art in artificial intelligence, gaining wide popularity from both industry and academia. Special interest is around Convolutional Neural Networks (CNN), which ...
Ponencia
Incremental Learning For Fundus Image Segmentation
(IARIA XPS Press, 2020-03-22)
Automated Fundus image segmentation is tradition-ally done in the image acquisition instrument and, thus, in thiscase it only needs to be able to segment data from this acquisitionsource. Cloud providers support multi GPU ...
Artículo
Comprehensive Evaluation of OpenCL-based Convolutional Neural Network Accelerators in Xilinx and Altera FPGAs
(Cornell University, 2016)
Deep learning has significantly advanced the state of the art in artificial intelligence, gaining wide popularity from both industry and academia. Special interest is around Convolutional Neural Networks (CNN), which take ...
Artículo
Deep Learning System for COVID-19 Diagnosis Aid Using X-ray Pulmonary Images
(MDPI, 2020)
The spread of the SARS-CoV-2 virus has made the COVID-19 disease a worldwide epidemic. The most common tests to identify COVID-19 are invasive, time consuming and limited in resources. Imaging is a non-invasive technique ...
Artículo
AnkFall—Falls, Falling Risks and Daily-Life Activities Dataset with an Ankle-Placed Accelerometer and Training Using Recurrent Neural Networks
(MDPI, 2021)
Falls are one of the leading causes of permanent injury and/or disability among the elderly. When these people live alone, it is convenient that a caregiver or family member visits them periodically. However, these visits ...
Artículo
COVID-XNet: a custom Deep Learning system to diagnose and locate COVID-19 in chest X-ray images
(MDPI, 2020-08)
The COVID-19 pandemic caused by the new coronavirus SARS-CoV-2 has changed the world as we know it. An early diagnosis is crucial in order to prevent new outbreaks and control its rapid spread. Medical imaging techniques, ...
Ponencia
Polyp Detection in Gastrointestinal Images using Faster Regional Convolutional Neural Network
(ScitePress Digital Library, 2019)
Colorectal cancer is the third most frequently diagnosed malignancy in the world. To prevent this disease, polyps, the principal precursor, are removed during a colonoscopy. Automatic detection of polyps in this technique ...