Intelligent Experiment Design-Based Virtual Remote Sensing Laboratory. - Yuriy Shkvarko; Stewart Santos; José Tuxpan (CIARP, 2009)

Unified Experiment Design, Bayesian Minimum Risk and Convex Projection Regularization Method for Enhanced Remote Sensing Imaging. - Yuriy Shkvarko; José Tuxpan; Stewart Santos (CIARP, 2009)

Fused variational analysis technique for high-resolution reconstruction of remote sensing imagery. - José Tuxpan-Vargas; Stewart René Santos Arce (CCE, 2010)

Resolution-enhanced radar/SAR imaging: an experiment design framework combined with neural network-adapted variational analysis regularization. - Yuriy Shkvarko; Stewart Santos; José Tuxpan (EURASIP J. Adv. Signal Process., 2011)

Dynamic Experiment Design Regularization Approach to Adaptive Imaging with Array Radar/SAR Sensor Systems. - Yuriy Shkvarko; José Tuxpan; Stewart Santos (Sensors, 2011)

High-resolution imaging with uncertain radar measurement data: A doubly regularized compressive sensing experiment design approach. - Yuriy V. Shkvarko; José Tuxpan; Stewart Santos; Israel Yañez (IGARSS, 2012)

Reconstruction of remote sensing imagery via fused multimode neural network computing. - Yuriy V. Shkvarko; Stewart Santos; José Tuxpan (CONIELECOMP, 2013)

ℓ2-ℓ1 Structured descriptive experiment design regularization based enhancement of fractional SAR imagery. - Yuriy V. Shkvarko; José Tuxpan; Stewart René Santos Arce (Signal Process., 2013)

Spatial spectrum pattern estimation based on the DEDR-TV extended approach for fractional SAR imagery enhancement. - David G. Torres; José Tuxpan; Israel Yañez (CONIELECOMP, 2014)

Dynamics of Multimodal Families of m-Modal Maps. - S. González-Salas; B. B. Cassal-Quiroga; José Tuxpan; Eric Campos (Complex., 2022)

Identification of Deep Convection Clouds Using ABIGOES Data and Machine Learning Techniques: The Case of Los Mochis, Sinaloa, Mexico. - Rodrigo Dávila-Ortiz; José Tuxpan-Vargas; Juan Alberto Velázquez-Zapata (ENC, 2023)

A systematic review and meta-analysis of groundwater level forecasting with machine learning techniques: Current status and future directions. - José Luis Uc-Castillo; Ana Elizabeth Marín-Celestino; Diego Armando Martínez-Cruz; José Tuxpan-Vargas; José Alfredo Ramos-Leal (Environ. Model. Softw., 2023)

A systematic review of Machine Learning and Deep Learning approaches in Mexico: challenges and opportunities. - José Luis Uc-Castillo; Ana Elizabeth Marín-Celestino; Diego Armando Martínez-Cruz; José Tuxpan-Vargas; José Alfredo Ramos-Leal; Janete Morán Ramírez (Frontiers Artif. Intell., 2024)

Alternative method to reveal encoded images via Gaussian distribution functions. - Marcial Bonilla-Marín; José Tuxpan; Eric Campos-Cantón (Integr., 2024)

Approximation of a Convective-Event-Monitoring System Using GOES-R Data and Ensemble ML Models. - Rodrigo Dávila-Ortiz; José Noel Carbajal-Pérez; Juan Alberto Velázquez-Zapata; José Tuxpan-Vargas (Remote. Sens., 2024)

An approach for accurate identification and monitoring of species in mangrove forests based on multi-source spectral data and deep learning. - Erandi Monterrubio-Martínez; Rubicel Trujillo-Acatitla; José Tuxpan-Vargas; Patricia Moreno-Casasola (Ecol. Informatics, 2025)