03138nas a2200397 a 4500 20260818085916.0 240229s20239999th u m tt 000 a eng d .b1242190x AIT RSPR no.DSAI-23-02 Aung Zar Lin Deep learning combined with homography based vision algorithm for trench dimension estimation Pathum Thani, Thailand : Asian Institute of Technology, 2023 27 leaves : ill. Research studies project report ; no. DSAI-23-02 A research study submitted in partial fulfillment of the requirements for the degree of Master of Science in Data Science and Artificial Intelligence, School of Engineering and Technology Research Studies Project Report (M. Sc.) - Asian Institute of Technology, 2023 One of the crucial components of the waterworks authority is the installation of water pipes. Water pipes that require less maintenance and last longer should be installed prop erly and in accordance with industry standards. To install a water pipe, the construction procedure begins by digging a trench that has a specific width and depth. Trench-digging errors, such as using the wrong width and depth for the trench or using incorrect trench profiles, will result in water pipe damage. That might eventually result in water pipe leaks, which are very challenging to find and correct. In my research, a single camera will be used to capture an image of the trench. The YOLO v4 object detection algorithm is used to detect the trench profile. A homography matrix calculation is performed to convert image coordinates to real world coordinates. There are many different ways to calculate a homography matrix. In this research, I create the homography from co-planar points. Using the homography, the dimensions of the trench can be estimated using Euclidean distance between points P1 and P2. The algorithm received the error less than 10 percent when the camera distance is less than 800 cm and the camera angle is less than 20 degrees. Deep learning (Machine learning) Trenchs Safety measures Data processing Dailey, Matthew N., Chairperson Mongkol Ekpanyapong, Examination Committee Chaklam Silpasuwanchai, Examination Committee AIT Fellowship, Scholarship Donor Asian Institute of Technology. Research studies project report ; no. DSAI-23-02 Full-Text http://203.159.5.9/ait-thesis/detail.php?q=B20426 .b1242190x mnait a 250307 0 240315 m a a 0 mnarc mnarc 67 40 Barcode : - CREATED : 2024-02-29 RECORD # : i1348817x LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : 30050120898779 CREATED : 2025-07-03 RECORD # : i13537581 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 26191 26191 0 0 0 0 MAIN MAIN mnarc 2026-08-18 0 AIT RSPR no.DSAI-23-02 2026-08-18 08:59:16 2026-08-18 67 0 0 0 0 MAIN MAIN mnarc 2026-08-18 0 AIT RSPR no.DSAI-23-02 30050120898779 2026-08-18 08:59:16 1 2026-08-18 40