PicQuest - Image Recognition Chatbot

The "Image-Based Chatbot" is an innovative advancement in conversational AI [8] that integrates visual understanding with natural language [3] processing to enhance user interactions. Unlike traditional text-based chatbots, which rely solely on written inputs, this chatbot leverages both images and text to process and generate responses, enabling a more intuitive and dynamic conversation. By incorporating image recognition capabilities, the system can analyze and interpret visual content such as photographs, diagrams, or sketches, allowing for richer, context-aware communication. This dual- modal interaction broadens the chatbot's application across industries such as customer support, e-commerce, education, and healthcare, where visual context plays a crucial role in user queries. This paper discusses the technological framework, potential use cases, and challenges of developing an image-based chatbot [2], offering insights into how it can reshape the landscape of human-computer interaction by providing more engaging, efficient, and versatile experiences.

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Publication Details

Published
2025-04-24
DOI
https://doi.org/10.38124/ijisrt/25apr848
Primary Topic
Information Retrieval and Data Mining
Type
article
Field-Weighted Citation Impact
0.00
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article

PicQuest - Image Recognition Chatbot

Ajitkumar Khachane, Tejas Patil, Sarvesh Pansare, Sahil Ukarde
Information Retrieval and Data Mining
article

PicQuest - Image Recognition Chatbot

Ajitkumar Khachane, Tejas Patil, Sarvesh Pansare, Sahil Ukarde
article en

Abstract

The "Image-Based Chatbot" is an innovative advancement in conversational AI [8] that integrates visual understanding with natural language [3] processing to enhance user interactions. Unlike traditional text-based chatbots, which rely solely on written inputs, this chatbot leverages both images and text to process and generate responses, enabling a more intuitive and dynamic conversation. By incorporating image recognition capabilities, the system can analyze and interpret visual content such as photographs, diagrams, or sketches, allowing for richer, context-aware communication. This dual- modal interaction broadens the chatbot's application across industries such as customer support, e-commerce, education, and healthcare, where visual context plays a crucial role in user queries. This paper discusses the technological framework, potential use cases, and challenges of developing an image-based chatbot [2], offering insights into how it can reshape the landscape of human-computer interaction by providing more engaging, efficient, and versatile experiences.

Openalex Percentile: Top 89%
Information Retrieval and Data Mining
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