Muhammad Usman

An Asynchronous Gradient Fusion Framework for Distributed Deep Learning in Tuberculosis Chest X-Ray Diagnosis

A Collaborative Gradient Fusion, a distributed deep learning framework designed to improve scalability and training stability in asynchronous environments, and introduces a version-aware aggregation strategy with bounded staleness control, along with adaptive batch-size tuning to reduce the impact of delayed gradients.