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The field is shifting toward Multimodal Large Language Models (MLLMs) to provide better reasoning and generative flexibility. Community Perspectives

The identifier refers to the specific article index for a prominent scientific review titled "Deep image captioning: A review of methods, trends and future challenges" , published in the journal Neurocomputing (Volume 546, August 2023).

There is a critical need to bridge the "visual-pathological gap," as many standard models lack the ability to accurately describe pathological locations. 126287

Using attention mechanisms to identify the most relevant parts of an image for a specific description.

Newer models like JAGAN (Joint Attention Generative Adversarial Nets) are introduced to ensure that the generated text maintains a professional "clinical language style". 📊 Key Challenges & Metrics The field is shifting toward Multimodal Large Language

Traditional training data can lead to hallucinations or biased outputs, particularly in socio-economically diverse content.

Experts and researchers emphasize the practical difficulties and recent breakthroughs in applying these deep reviews to real-world medical data. Using attention mechanisms to identify the most relevant

This review provides a systematic and comprehensive analysis of how deep learning models translate visual content into human language, with a particular focus on both general and medical applications. 🔬 Core Components of the Review