Writer Adaption for Handwritten Text Recognition of Historical Documents
Status: available Supervisors: Marco Peer The digitization and preservation of historical documents rely on accurate transcription of handwritten text. However, historical documents often present unique challenges due to variations in writing styles and deteriorated conditions. This thesis should explore the concepts of writer identification and writer-specific style extraction within Handwritten Text Recognition (HTR) systems, focusing … Continue reading Writer Adaption for Handwritten Text Recognition of Historical Documents