Computer Vision (CV) models are at the forefront of transforming how machines interact with and understand visual data. From autonomous vehicles to medical imaging, CV is enabling groundbreaking advancements. However, challenges like enhancing accuracy in complex environments, real-time processing, and scalability still remain.
The current focus is on improving model efficiency, reducing computational overhead, and boosting generalization across diverse scenarios. The goal is to develop CV systems that are not only faster and more reliable but also capable of operating effectively in dynamic and resource-constrained environments.