Broad Adaptability of Coronavirus Adhesion Revealed from the Complementary Surface Affinity of Membrane and Spikes

Autor: Aritz B. García‐Arribas, Pablo Ibáñez‐Freire, Diego Carlero, Pablo Palacios‐Alonso, Miguel Cantero‐Reviejo, Pablo Ares, Guillermo López‐Polín, Han Yan, Yan Wang, Soumya Sarkar, Manish Chhowalla, Hanna M. Oksanen, Jaime Martín‐Benito, Pedro J. de Pablo, Rafael Delgado‐Buscalioni

Publikováno v: Advanced Science, Vol 11, Iss 41, Pp n/a-n/a (2024)

Abstract Coronavirus stands for a large family of viruses characterized by protruding spikes surrounding a lipidic membrane adorned with proteins. The present study explores the adhesion of transmissible gastroenteritis coronavirus (TGEV) particles o

Externí odkaz: https://doaj.org/article/d6182c7e743b4059a3bf8d330057d4f0

Feature Representation in Deep Metric Embeddings

Autor: Furlong, Ryan, O'Brien, Vincent, Garland, James, Palacios-Alonso, Daniel, Dominguez-Mateos, Francisco

In deep metric learning (DML), high-level input data are represented in a lower-level representation (embedding) space, such that samples from the same class are mapped close together, while samples from disparate classes are mapped further apart. In

Externí odkaz: http://arxiv.org/abs/2102.03176

Facial mask-wearing prediction and adaptive gender classification using convolutional neural networks

Autor: Mohamed Oulad-Kaddour, Hamid Haddadou, Daniel Palacios-Alonso, Cristina Conde, Enrique Cabello

Publikováno v: EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, Vol 11, Iss 2 (2024)

The world has lived an exceptional time period caused by the Coronavirus pandemic. To limit Covid-19 propagation, governments required people to wear a facial mask outside. In facial data analysis, mask-wearing on the human face creates predominant o

Externí odkaz: https://doaj.org/article/e9981e38005c4cf189f1ff843a5241a1

Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends

Autor: Górriz, J.M., Álvarez-Illán, I., Álvarez-Marquina, A., Arco, J.E., Atzmueller, M., Ballarini, F., Barakova, E., Bologna, G., Bonomini, P., Castellanos-Dominguez, G., Castillo-Barnes, D., Cho, S.B., Contreras, R., Cuadra, J.M., Domínguez, E., Domínguez-Mateos, F., Duro, R.J., Elizondo, D., Fernández-Caballero, A., Fernandez-Jover, E., Formoso, M.A., Gallego-Molina, N.J., Gamazo, J., González, J. García, Garcia-Rodriguez, J., Garre, C., Garrigós, J., Gómez-Rodellar, A., Gómez-Vilda, P., Graña, M., Guerrero-Rodriguez, B., Hendrikse, S.C.F., Jimenez-Mesa, C., Jodra-Chuan, M., Julian, V., Kotz, G., Kutt, K., Leming, M., de Lope, J., Macas, B., Marrero-Aguiar, V., Martinez, J.J., Martinez-Murcia, F.J., Martínez-Tomás, R., Mekyska, J., Nalepa, G.J., Novais, P., Orellana, D., Ortiz, A., Palacios-Alonso, D., Palma, J., Pereira, A., Pinacho-Davidson, P., Pinninghoff, M.A., Ponticorvo, M., Psarrou, A., Ramírez, J., Rincón, M., Rodellar-Biarge, V., Rodríguez-Rodríguez, I., Roelofsma, P.H.M.P., Santos, J., Salas-Gonzalez, D., Salcedo-Lagos, P., Segovia, F., Shoeibi, A., Silva, M., Simic, D., Suckling, J., Treur, J., Tsanas, A., Varela, R., Wang, S.H., Wang, W., Zhang, Y.D., Zhu, H., Zhu, Z., Ferrández-Vicente, J.M.

Publikováno v: In Information Fusion December 2023 100

Deep Learning-Based Gender Classification by Training With Fake Data

Autor: Mohamed Oulad-Kaddour, Hamid Haddadou, Cristina Conde Vilda, Daniel Palacios-Alonso, Karima Benatchba, Enrique Cabello

Publikováno v: IEEE Access, Vol 11, Pp 120766-120779 (2023)

Gender classification of human faces is a trending topic and a remarkable biometric task. This research area has useful applications in several fields, such as automated border control (ABC) and forensic work. There are many approaches to gender clas

Externí odkaz: https://doaj.org/article/5fe94199a9c34c32b9790d001708854b