Cynthia Akanaga developed foundational facial expression recognition capabilities for the beyond-the-pixels-emerging-computer-vision-research-topics-fa24 repository, focusing on reproducible research workflows. She implemented a TensorFlow-based core model using a ResNet50 backbone, handling data loading, preprocessing, and training scaffolding in Python and Jupyter Notebook. Cynthia also established a bias analysis and visualization framework centered on the UTKFace dataset, providing detailed documentation and interactive notebooks to support bias detection and evaluation. Her work emphasized repository hygiene, reproducibility, and collaborative readiness, resulting in a robust baseline for future research and feature development in computer vision, data analysis, and deep learning within the project.
November 2024: Delivered foundational FER capabilities and bias-analysis workflow in the beyond-the-pixels CV project. Established a TensorFlow-based Facial Expression Recognition (FER) core model with ResNet50 backbone, including data loading, preprocessing, training scaffolding, and core documentation. Implemented a bias-analysis visualization and documentation workflow centered on UTKFace, with notebooks and updated READMEs. Improved repository hygiene through notebook creation/cleanup and documentation updates, setting up reproducibility and collaboration for future sprints.
November 2024: Delivered foundational FER capabilities and bias-analysis workflow in the beyond-the-pixels CV project. Established a TensorFlow-based Facial Expression Recognition (FER) core model with ResNet50 backbone, including data loading, preprocessing, training scaffolding, and core documentation. Implemented a bias-analysis visualization and documentation workflow centered on UTKFace, with notebooks and updated READMEs. Improved repository hygiene through notebook creation/cleanup and documentation updates, setting up reproducibility and collaboration for future sprints.
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