Zero-shot learning: Using text to more accurately identify images

Introduced a novel generative adversarial zero-shot learning (GAZSL) model that uses GANs to identify objects described in text. This model extracts visual features from text, creates synthetic visualizations, and uses them to classify objects it hasn't been trained on. Tested against seven other ZSL algorithms, GAZSL achieved 4-7% higher accuracy across four benchmarks, demonstrating a more accurate and generalizable approach to computer vision.