Conversational Image Recognition Chatbot

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Subhash N; N Sultan Basha; Abhishek A; Shaik Nihal Basha; Dr.Joseph Michael Jerard V

Conversational Image Recognition Chatbot

Authors: Subhash N, N Sultan Basha, Abhishek A, Shaik Nihal Basha, Dr.Joseph Michael Jerard V

Unique Paper ID: 178720
Volume: 11
Issue: 12
PageNo: 5559-5561

Keywords: Conversational AI Image Recognition Multimodal Interaction Google Vision API GPT-4o Visual Question Answering (VQA) Natural Language Processing (NLP) Human-Computer Interaction Deep Learning Image Captioning Chatbot Vision-Language Models Streamlit Application AI-Powered Assistants Contextual Response Generation.

Abstract:
Conversational image recognition chatbots represent a compelling fusion of computer vision and natural language processing (NLP), enabling users to engage in dynamic, human-like dialogue centered around visual content. These systems can analyze images and provide meaningful descriptions, answer context-specific questions, or even infer abstract concepts—facilitating intuitive human-computer interaction across diverse domains, such as education, healthcare, e-commerce, and accessibility. Leveraging deep learning models like convolutional neural networks (CNNs) for image understanding and transformer-based architectures for language generation, these chatbots bridge the gap between visual and linguistic intelligence. This paper explores the design, architecture, and implementation of such systems, emphasizing the integration of vision-language models, multimodal datasets, and dialogue management strategies. We also address challenges related to accuracy, contextual understanding, bias mitigation, and real-time performance. By examining current advancements and potential future directions, this research highlights the transformative potential of conversational image recognition systems in creating more accessible and intelligent interfaces.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 12
PageNo: 5559-5561

Conversational Image Recognition Chatbot

Available:https://ijirt.org/article?manuscript=178720

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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