In image captioning, the challenge lies in creating coherent textual descriptions for images. Traditionally, image descriptions have been limited to single-word annotations based on object detection. Recent progress mainly relies on deep learning, notably Encoder-Decoder models that integrate Convolutional Neural Networks for feature extraction. However, there's limited exploration into integrating object detection features. An AI model, employing a regenerative neural architecture, seamlessly merges computer vision and NLP to autonomously generate descriptive phrases for images. By utilizing Convolutional Neural Networks and Recurrent Neural Networks the model accurately and fluently describes images, showcasing linguistic proficiency and comprehension of visual content. Evaluations across diverse datasets consistently validate the model's efficacy in delivering precise and articulate image descriptions.