Browsing by Author "Moya Sánchez, Eduardo Ulises"
Now showing items 1-9 of 9
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A bio-inspired quaternion local phase CNN layer with contrast invariance and linear sensitivity to rotation angles
(Elsevier, 2020-03)
Article
Open AccessDeep learning models have been particularly successful with image recognition using Convolutional Neural Networks (CNN). However, the learning of a contrast invariance and rotation equivariance response may fail even with ... -
A quaternion deterministic monogenic CNN layer for contrast invariance
(Springer, 2021)
Part of book or chapter of book
Open AccessDeep learning (DL) is attracting considerable interest as it currently achieves remarkable performance in many branches of science and technology. However, current DL cannot guarantee capabilities of the mammalian visual ... -
A trainable monogenic ConvNet layer robust in front of large contrast changes in image classification
(Institute of Electrical and Electronics Engineers (IEEE), 2021-12-20)
Article
Open AccessConvolutional Neural Networks (ConvNets) at present achieve remarkable performance in image classification tasks. However, current ConvNets cannot guarantee the capabilities of the mammalian visual systems such as invariance ... -
Artificial intelligence to identify retinal fundus images, quality validation, laterality evaluation, macular degeneration, and suspected glaucoma
(2020-02-13)
Article
Open AccessPurpose: To assess the performance of deep learning algorithms for different tasks in retinal fundus images: (1) detection of retinal fundus images versus optical coherence tomography (OCT) or other images, (2) evaluation ... -
Automatic vehicle counting area creation based on vehicle deep learning detection and DBSCAN
(Institute of Electrical and Electronics Engineers (IEEE), 2022)
Conference report
Open AccessDeep learning and high-performance computing have augmented and speed-up the scope of video-based vehicles' massive counting. The automatic vehicle counts result from the detection and tracking of the vehicles in certain ... -
Data augmentation for deep learning of non-mydriatic screening retinal fundus images
(Springer, 2018)
Conference report
Restricted access - publisher's policyFundus image is an effective and low-cost tool to screen for common retinal diseases. At the same time, Deep Learning (DL) algorithms have been shown capable of achieving similar or even better performance accuracies than ... -
Detection, counting, and classification of visual ganglia columns of drosophila pupae
(2019)
Article
Open AccessMany neurobiologists use the fruit fly (Drosophila) as a model to study neuron interaction and neuron organization and then extrapolate this knowledge to the nature of human neurological disorders. Recently, the fluorescence ... -
Etiquetado, clasificación y análisis de calidad de imagen para detección de retinopatía diabética usando modelos convolucionales profundos
(2023)
Article
Open AccessLa retinopatía diabética (RD) es la principal causa de ceguera en el mundo en edad laboral. La detección-tratamiento temprano ha demostrado ser efectiva para disminuir las complicaciones visuales (y la ceguera) de los ... -
To be fAIr or not to be: using AI for the good of citizens
(2021-03)
Article
Open AccessIn the last decade, there has been an explosion in the progress and applications of artificial intelligence (AI) in our society. For the first time, the applications of AI have left the laboratory to reach society in a ...
