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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 ...
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Liquid State Machine on SpiNNaker for Spatio-Temporal Classification Tasks
(Frontiers Media S.A., 2022-03-14)
Liquid State Machines (LSMs) are computing reservoirs composed of recurrently connected Spiking Neural Networks which have attracted research interest for their modeling capacity of biological structures and as promising ...
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Dual Machine-Learning system to aid Glaucoma Diagnosis using disc and cup feature extraction.
(IEEE Computer Society, 2020)
Glaucoma is a degenerative disease that affects vision, causing damage to the optic nerve that ends in vision loss. The classic techniques to detect it have undergone a great change since the intrusion of machine learning ...
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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 ...
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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 ...
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Five years of designing wireless sensor networks in the Doñana Biological Reserve (Spain): an applications approach
(2013)
Wireless Sensor Networks (WSNs) are a technology that is becoming very popular for many applications, and environmental monitoring is one of its most important application areas. This technology solves the lack of flexibility ...
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Real-time detection of uncalibrated sensors using neural networks
(Springer, 2022)
Nowadays, sensors play a major role in several fields, such as science, industry and everyday technology. Therefore, the information received from the sensors must be reliable. If the sensors present any anomalies, serious ...
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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 ...
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A Research Roadmap: Connected Health as an Enabler of Cancer Patient Support
(JMIR Publications, 2019)
The evidence that quality of life is a positive variable for the survival of cancer patients has prompted the interest of the health and pharmaceutical industry in considering that variable as a final clinical outcome. ...
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Securing a wireless sensor network for human tracking: a review of solutions
(Wiley, 2014)
Currently, wireless sensor networks (WSNs) are formed by devices with limited resources and limited power energy availability. Thanks to their cost effectiveness, flexibility, and ease of deployment, wireless sensor ...