Buscar
Mostrando ítems 1-10 de 22
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 ...
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 ...
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
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
Wide and Deep neural network model for patch aggregation in CNN-based prostate cancer detection systems
(Elsevier, 2021)
Prostate cancer (PCa) is one of the most commonly diagnosed cancer and one of the leading causes of death among men, with almost 1.41 million new cases and around 375,000 deaths in 2020. Artificial Intelligence algorithms ...
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 ...