Image Analytics for Legal Document Review: A Transfer Learning Approach
This addresses the need for advanced image analytics in the legal industry, but it is incremental as it adapts existing transfer learning methods to a new domain.
The paper tackles the problem of analyzing multimedia content in legal document review by applying deep learning for image classification, clustering, and object detection, demonstrating effectiveness in real-world business challenges.
Though technology assisted review in electronic discovery has been focusing on text data, the need of advanced analytics to facilitate reviewing multimedia content is on the rise. In this paper, we present several applications of deep learning in computer vision to Technology Assisted Review of image data in legal industry. These applications include image classification, image clustering, and object detection. We use transfer learning techniques to leverage established pretrained models for feature extraction and fine tuning. These applications are first of their kind in the legal industry for image document review. We demonstrate effectiveness of these applications with solving real world business challenges.