• Nishant Arora
• Suhani Talesara
• Shashwat Sharma
• Dr.Mayank Patel

This paper presents a novel approach to integrating image recognition with conversational AI, resulting in a chatbot capable of understanding and responding to user queries based on uploaded images. Leveraging YOLOv8 for object detection and BERT for natural language understanding, the proposed system can detect multiple objects in a group image, extract them, and provide accurate answers to user questions about these objects. The fusion of these two advanced AI technologies allows for an intuitive and accessible tool that simplifies image interpretation through conversation. Furthermore, the system demonstrates exceptional performance in real-time detection scenarios with complex industrial imagery, achieving high precision and recall rates across various lighting conditions and object densities. Extensive testing with domain experts validates the system's practical utility in reducing analysis time by up to 78% compared to manual inspection methods. This research contributes toward creating intuitive, accessible AI tools for industrial monitoring, education, healthcare, and other visual-centric domains, with particular emphasis on enhancing human-machine interaction through multimodal communication channels.

CONVERSATIONAL IMAGE RECOGNITION CHATBOT

"CONVERSATIONAL IMAGE RECOGNITION CHATBOT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 6, page no.302-308, June-2025, Available :http://www.jetir.org/papers/JETIRGW06049.pdf

"CONVERSATIONAL IMAGE RECOGNITION CHATBOT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 6, page no. pp302-308, June-2025, Available at : http://www.jetir.org/papers/JETIRGW06049.pdf