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Mostrando ítems 1-10 de 12
Ponencia
Multidataset Incremental Training for Optic Disc Segmentation
(Springer, 2020)
When convolutional neural networks are applied to image segmentation results depend greatly on the data sets used to train the networks. Cloud providers support multi GPU and TPU virtual machines making the idea of ...
Ponencia
Glioma Diagnosis Aid through CNNs and Fuzzy-C Means for MRI
(ScitePress Digital Library, 2019)
Glioma is a type of brain tumor that causes mortality in many cases. Early diagnosis is an important factor. Typically, it is detected through MRI and then either a treatment is applied, or it is removed through ...
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
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 ...
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 ...
Ponencia
An Automated Fall Detection System Using Recurrent Neural Networks
(Springer, 2019)
Falls are the most common cause of fatal injuries in elderly people, causing even death if there is no immediate assistance. Fall detection systems can be used to alert and request help when this type of accident happens. ...
Ponencia
Event-based Row-by-Row Multi-convolution engine for Dynamic-Vision Feature Extraction on FPGA
(IEEE Computer Society, 2018)
Neural networks algorithms are commonly used to recognize patterns from different data sources such as audio or vision. In image recognition, Convolutional Neural Networks are one of the most effective techniques due ...
Ponencia
Sampling Frequency Evaluation on Recurrent Neural Networks Architectures for IoT Real-time Fall Detection Devices
(ScitePress Digital Library, 2019)
Falls are one of the most frequent causes of injuries in elderly people. Wearable Fall Detection Systems provided a ubiquitous tool for monitoring and alert when these events happen. Recurrent Neural Networks (RNN) are ...
Ponencia
Breast Cancer Automatic Diagnosis System using Faster Regional Convolutional Neural Networks
(ScitePress Digital Library, 2019)
Breast cancer is one of the most frequent causes of mortality in women. For the early detection of breast cancer, the mammography is used as the most efficient technique to identify abnormalities such as tumors. ...