像素到散文：理解图像描述的艺术
Pixels to Prose: Understanding the art of Image Captioning
AI总结：
本文全面回顾了图像描述技术从基础架构到前沿方法的演变，剖析其底层机制、医疗领域应用及性能评估指标，为机器学习初学者提供理论结合实践的导航指南。
摘要：
在人工智能不断发展的时代，机器正越来越多地模仿类人能力，包括视觉感知和语言表达。图像描述（Image Captioning）处于这些领域的交汇处，使机器能够解释视觉内容并生成描述性文本。本文对图像描述技术进行了全面回顾，适合那些刚进入机器学习领域并希望全面了解从基础方法到最先进方法的可用选项的人。从探索原始架构开始，本回顾追溯了图像描述模型向最新前沿解决方案的演变。通过剖析这些架构的组件，读者可以深入了解其底层机制，并根据特定问题需求选择合适的方法，而无需重复劳动。本文还深入探讨了图像描述在医疗领域的应用，阐明了其在各种现实场景中的重要性。此外，本回顾提供了关于评估图像描述系统性能的指导，强调了用于评估的关键指标。通过将理论概念与实际应用相结合，本文为读者提供了所需的知识，以驾驭图像描述的复杂格局，并利用其在机器学习及更广泛领域的各种应用中的潜力。
英文摘要：
In the era of evolving artificial intelligence, machines are increasingly emulating human-like capabilities, including visual perception and linguistic expression. Image captioning stands at the intersection of these domains, enabling machines to interpret visual content and generate descriptive text. This paper provides a thorough review of image captioning techniques, catering to individuals entering the field of machine learning who seek a comprehensive understanding of available options, from foundational methods to state-of-the-art approaches. Beginning with an exploration of primitive architectures, the review traces the evolution of image captioning models to the latest cutting-edge solutions. By dissecting the components of these architectures, readers gain insights into the underlying mechanisms and can select suitable approaches tailored to specific problem requirements without duplicating efforts. The paper also delves into the application of image captioning in the medical domain, illuminating its significance in various real-world scenarios. Furthermore, the review offers guidance on evaluating the performance of image captioning systems, highlighting key metrics for assessment. By synthesizing theoretical concepts with practical application, this paper equips readers with the knowledge needed to navigate the complex landscape of image captioning and harness its potential for diverse applications in machine learning and beyond.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
