Marvella I. Oros-Flores
Papers
1
Total Citations
109
H-Index
1
About
Marvella I. Oros-Flores is a leading researcher in human activity recognition and deep learning architectures, with a particular focus on temporal convolutional neural networks. Her most-cited work, "Human activity recognition using temporal convolutional neural network architecture" (2021), has garnered 109 citations, establishing her as a key contributor to the field of sensor-based human behavior analysis. Oros-Flores’s major contribution lies in developing novel temporal convolutional network designs that effectively capture long-range dependencies in sequential data, significantly improving the accuracy and efficiency of activity recognition systems. Her research has practical implications for healthcare monitoring, smart environments, and assistive technologies, where reliable human activity detection is critical. Beyond her citation impact, Oros-Flores is recognized for bridging the gap between theoretical deep learning advancements and real-world applications, making her work highly influential among both academic and industrial researchers. Her achievements include collaborations on interdisciplinary projects that integrate computer vision and wearable sensor data, further demonstrating her versatility and commitment to advancing human-centered computing.
Research Focus
Key Achievements
Top Papers
- 1