Forensic Analysis of Contents in Thumbnails Using Transfer Learning

Thumbnails accelerate the concise description of a collection of images that iterate through large datasets till it trains our deep learning model to capture the text-whitened thumbnails. Many court cases and forensic investigations have involved thumbnail pictures within laptops or mobile devices. Millions of thumbnails are often ready for digital forensics experts to export. Machine learning can quickly help identify an investigation’s targets. Text or objective recognition is a primary study solution for document digitization and forensic analysis. Inspired by the recent success of Transformer in many applications, in this paper, we adopt design transfer learning as an effective method of achieving excellent performance with a noisy training of dataset of thumbnails. This deep learning model aims to investigate the pre-trained model in the Torch Vision package employing tensors and Cuda-GPU parallel computing to emphasize the OCR (Optical Character Recognition) system engine. We report the preliminary results of our methods to help digital forensics experts to identify their targets robustly and efficiently.