abstract
- Most patent retrieval systems are text-based, which under utilizes the multimodal nature of patent documents. Although a few multimodal patent retrieval systems exist, they fall short in providing efficient and informative visualizations, and facilitating the interpretation of retrieval results. To address these shortcomings, this paper presents iPatent, a novel web-based multimodal patent image retrieval system. Unlike previous solutions, iPatent integrates state-of-the-art deep learning models for fine-grained unimodal, cross-modal, and multimodal patent image retrieval. Additionally, it employs both traditional machine learning techniques and modern generative methods for interactive visual exploration and insightful interpretation of retrieval results. iPatent leverages modern web technologies to provide an interactive interface that enables users to explore large patent databases efficiently and in a visually informative way. Source code and demo are publicly available at: https://service.tib.eu/ipatent/