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Mostrando ítems 1-10 de 17
Artículo
Deep Neural Networks for the Recognition and Classification of Heart Murmurs Using Neuromorphic Auditory Sensors
(IEEE Computer Society, 2017)
Auscultation is one of the most used techniques for detecting cardiovascular diseases, which is one of the main causes of death in the world. Heart murmurs are the most common abnormal finding when a patient visits the ...
Artículo
Non-small cell lung cancer diagnosis aid with histopathological images using Explainable Deep Learning techniques
(Elsevier, 2022-11)
Background: Lung cancer has the highest mortality rate in the world, twice as high as the second highest. On the other hand, pathologists are overworked and this is detrimental to the time spent on each patient, diagnostic ...
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 ...
Artículo
Efficient Memory Organization for DNN Hardware Accelerator Implementation on PSoC
(MDPI, 2021-01)
The use of deep learning solutions in different disciplines is increasing and their algorithms are computationally expensive in most cases. For this reason, numerous hardware accelerators have appeared to compute their ...
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
A study on the use of Edge TPUs for eye fundus image segmentation
(Elsevier, 2021)
Medical image segmentation can be implemented using Deep Learning methods with fast and efficient segmentation networks. Single-board computers (SBCs) are difficult to use to train deep networks due to their memory and ...
Artículo
Does Two-Class Training Extract Real Features? A COVID-19 Case Study
(MDPI, 2021-01)
Diagnosis aid systems that use image analysis are currently very useful due to the large workload of health professionals involved in making diagnoses. In recent years, Convolutional Neural Networks (CNNs) have been used ...
Artículo
A lightweight xAI approach to cervical cancer classification
(Springer, 2024-03)
Cervical cancer is caused in the vast majority of cases by the human papilloma virus (HPV) through sexual contact and requires a specific molecular-based analysis to be detected. As an HPV vaccine is available, the incidence ...
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
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 ...