Object Detection and Recognition Using YOLO: Detect and Recognize URL(s) in an Image Scene

The world in the 21st century is ever evolving towards automation. This upsurge seemingly has no decline in the foreseeable future. Image recognition is at the forefront of this charge which seeks to revolutionize the way of living of the average man. If robotics can be likened to the creation of a body for computers to live in, then image processing is the development of the part of its brain which deal with identification and recognition of images. To accomplish this task, we developed an object detection algorithm using YOLO, and acronym for “You Only Look Once”. Our algorithm was trained on fifty thousand images and evaluated on ten thousand images and employed a 21 x 21 grid. We also programmed a text generator which randomly creates texts and URLs in an image. A record of useful information about the location of the URLs in the image is also recorded and later passed to the YOLO algorithm for training. At the end of this project, we observed significant difference in the accuracy of URL detection when using an OCR software or our YOLO algorithm. However, our algorithm would be best used to specify the region of interest before converting to texts which greatly improves accuracy when combined with OCR software

Industry/University Collaboration at the University of Michigan-Dearborn: A Focus on Relevant Technology

https://deepblue.lib.umich.edu/bitstream/2027.42/154105/1/kampfner1997.pd

A Web-based environment for automated dental identification research

The Criminal Justice Information Services (CJIS), division of the Federal Bureau of Investigations (FBI), include in its strategic plan the creation of an Automated Dental Identification System (ADIS), a Post Mortem Dental Identification System.;This project aims at designing an end-to-end web-interface to meet the requirements of ADIS like Identification, Maintenance and Bridge Modules. In Identification Mode the subject record will be uploaded by the user and the match list is obtained as result. Maintenance Mode enables uploading of reference records and to populate the database with preprocessing data. Bridge Module enables researchers from other universities to use the database designed in WVU. A database is also designed to hold non-dental features like name, age, gender etc and dental features like preprocessing data.;This provides the FBI agents and the Forensic experts the ability to use ADIS from their office desks. This web interface provides an Identification Module, Maintenance Module and Bridge Module. (Abstract shortened by UMI.)