Reinel Tabares-Soto
Orcid: 0000-0002-4978-5211
According to our database1,
Reinel Tabares-Soto
authored at least 19 papers
between 2019 and 2024.
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Bibliography
2024
A comparative study of CNN-capsule-net, CNN-transformer encoder, and Traditional machine learning algorithms to classify epileptic seizure.
BMC Medical Informatics Decis. Mak., December, 2024
Applying the ethics of AI: a systematic review of tools for developing and assessing AI-based systems.
Artif. Intell. Rev., May, 2024
CVTStego-Net: A convolutional vision transformer architecture for spatial image steganalysis.
J. Inf. Secur. Appl., 2024
2023
Inpactor2: a software based on deep learning to identify and classify LTR-retrotransposons in plant genomes.
Briefings Bioinform., January, 2023
Classification of Alzheimer's disease stages from magnetic resonance images using deep learning.
PeerJ Comput. Sci., 2023
Requests classification in the customer service area for software companies using machine learning and natural language processing.
PeerJ Comput. Sci., 2023
Enhancing Intrusion Detection in IoT Communications Through ML Model Generalization With a New Dataset (IDSAI).
IEEE Access, 2023
SAM-UNETR: Clinically Significant Prostate Cancer Segmentation Using Transfer Learning From Large Model.
IEEE Access, 2023
2022
Automatic curation of LTR retrotransposon libraries from plant genomes through machine learning.
J. Integr. Bioinform., 2022
Machine learning approaches for COVID-19 detection from chest X-ray imaging: A Systematic Review.
CoRR, 2022
Coffee Maturity Classification Using Convolutional Neural Networks and Transfer Learning.
IEEE Access, 2022
2021
PeerJ Comput. Sci., 2021
Strategy to improve the accuracy of convolutional neural network architectures applied to digital image steganalysis in the spatial domain.
PeerJ Comput. Sci., 2021
PeerJ Comput. Sci., 2021
GBRAS-Net: A Convolutional Neural Network Architecture for Spatial Image Steganalysis.
IEEE Access, 2021
Proceedings of the Sustainable Smart Cities and Territories, 2021
Proceedings of the Practical Applications of Computational Biology & Bioinformatics, 2021
2020
A comparative study of machine learning and deep learning algorithms to classify cancer types based on microarray gene expression data.
PeerJ Comput. Sci., 2020
2019
IEEE Access, 2019