Daniel Sierra-Sosa

Assistant Professor

Hood College

United States

Research Interests

Explore related searches

Professors in United States

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Daniel Sierra-Sosa is an Assistant Professor at Hood College in the United States. His research focuses on various areas including atmospheric turbulence, video classification in echocardiography, quantum transfer learning, pedestrian tracking, and smart city optimization. He has published several articles that explore the integration of classical and quantum methodologies in biomedical applications, as well as innovative techniques in data processing and machine learning.

Articles (12)

Year:

2025

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Collaborators (3)

Marielle Morissens

Université libre de Bruxelles

BELGIUM

View details

Adel Elmaghraby

Director of Industrial Research and Innovation , JB School of Engineering, Winnia Professor and Department Chair

University of Louisville

UNITED STATES

View details

Begonya Garcia-Zapirain

University of Deusto

SPAIN

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Daniel Sierra-Sosa

Research Interests

Explore related searches

Contact this professor

About

Articles (12)

Automatic Quantification of Atmospheric Turbulence Intensity in Space-Time Domain

Transfer Learning Video Classification of Preserved, Mid-Range, and Reduced Left Ventricular Ejection Fraction in Echocardiography

A Robust Pedestrian Re-Identification and Out-Of-Distribution Detection Framework

Hybrid Classical–Quantum Transfer Learning for Cardiomegaly Detection in Chest X-rays

Data rotation and its influence on quantum encoding

Directional Statistics-Based Deep Metric Learning for Pedestrian Tracking and Re-Identification

Making Cities Smarter—Optimization Problems for the IoT Enabled Smart City Development: A Mapping of Applications, Objectives, Constraints

Multi-layer data integration technique for combining heterogeneous crime data

A Deep Convolutional Neural Network-XGB for Direction and Severity Aware Fall Detection and Activity Recognition

Quantum Machine Learning Applications in the Biomedical Domain: A Systematic Review

Variational Quantum Classifier for Binary Classification: Real vs Synthetic Dataset

A Hierarchical Approach to Activity Recognition and Fall Detection Using Wavelets and Adaptive Pooling

Collaborators (3)

Marielle Morissens

Adel Elmaghraby

Begonya Garcia-Zapirain

Make your next move.