Abstract
This comprehensive literature review examines the latest breakthroughs in computer vision and natural language processing (NLP), two rapidly evolving fields with applications across search, human-computer interaction, robotics, and more. It synthesizes key findings, trends, limitations, and open challenges from cutting-edge research at their intersection. The dramatic progress driven by deep neural networks is analysed in depth, along with issues like generalization, context handling, reasoning, uncertainty, and human-centric evaluation. Although remarkable advances have been made, especially in computer vision, core problems remain to be addressed. This review provides a thorough overview of the state-of-the-art, reflecting the most recent innovations, and promising future directions in this dynamic research domain.
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