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Probing the Efficacy of Hardware-Aware Weight Pruning to Optimize the SpMM routine on Ampere GPUs
(Institute of Electrical and Electronics Engineers, 2022)
[Abstract]: The Deep Learning (DL) community found in pruning techniques a good way to reduce the models' resource and energy consumption. These techniques lead to smaller sparse models, but sparse computations in GPUs ...
Does imbalance in chest X-ray datasets produce biased deep learning approaches for COVID-19 screening?
(BMC, 2022)
[Abstract] Background
The health crisis resulting from the global COVID-19 pandemic highlighted more than ever the need for rapid, reliable and safe methods of diagnosis and monitoring of respiratory diseases. To study ...
Using Artificial Vision Techniques for Individual Player Tracking in Sport Events
(M D P I AG, 2019-07-31)
[Abstract] We introduce a hybrid approach that can track an individual football player in a video sequence. This solution achieves a good balance between speed and accuracy, combining traditional object tracking techniques ...
Intraretinal Fluid Detection by Means of a Densely Connected Convolutional Neural Network Using Optical Coherence Tomography Images
(MDPI AG, 2019-08-01)
[Abstract] Hereby we present a methodology with the objective of detecting retinal fluid accumulations in between the retinal layers. The methodology uses a robust Densely Connected Neural Network to classify thousands of ...
Paired and Unpaired Deep Generative Models on Multimodal Retinal Image Reconstruction
(M D P I AG, 2019-08-07)
[Abstract] This work explores the use of paired and unpaired data for training deep neural networks in the multimodal reconstruction of retinal images. Particularly, we focus on the reconstruction of fluorescein angiography ...
System for Automatic Assessment of Alzheimer’s Disease Diagnosis Based on Deep Learning Techniques
(M D P I AG, 2019-08-21)
[Abstract] Automatic detection of Alzheimer’s disease is a very active area of research. This is due to its usefulness in starting the protocol to stop the inevitable progression of this neurodegenerative disease. This ...
Automatic Assessment of Alzheimer’s Disease Diagnosis Based on Deep Learning Techniques
(Elsevier, 2020-05)
[Abstract]
Early detection is crucial to prevent the progression of Alzheimer’s disease (AD). Thus, specialists can begin preventive treatment as soon as possible. They demand fast and precise assessment in the diagnosis ...
Self-Supervised Multimodal Reconstruction Pre-training for Retinal Computer-Aided Diagnosis
(Elsevier, 2021)
[Abstract] Computer-aided diagnosis using retinal fundus images is crucial for the early detection of many ocular and systemic diseases. Nowadays, deep learning-based approaches are commonly used for this purpose. However, ...
A scalable saliency-based feature selection method with instance-level information
(Elsevier, 2019-11)
[Abstract]: Classic feature selection techniques remove irrelevant or redundant features to achieve a subset of relevant features in compact models that are easier to interpret and so improve knowledge extraction. Most ...
AI-based user authentication reinforcement by continuous extraction of behavioral interaction features
(Springer, 2022-07)
[Abstract]: In this work, we conduct an experiment to analyze the feasibility of a continuous authentication method based on the monitorization of the users' activity to verify their identities through specific user profiles ...