Leila Character
Biographic Data
| ID | 6452911 |
|---|---|
| NAME | Leila Character |
| GIVEN NAMES | Leila |
| FAMILY NAME | Character |
| SIGNATURE | CHARACTER L |
| AFFILIATIONS | Sam Houston State University |
| ORCID | 0000-0001-8763-6068 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 4 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Deep Learning for Detection of Underwater Aircraft Wrecks from US Conflicts
There are more than 72,000 missing in action service members from WWII, many of whom were lost at sea in aircraft. Using high-resolution sidescan sonar and a YOLOv7 model, we present a deep learning approach to expedite the search for these individuals. Our training dataset is the largest aircraft wreck-focused dataset that has been published to date, with 19 unique aircraft wrecks, composed of 290 individual fragments and located across six coun…
Documenting the First Three U.S. Aircraft Discovered in Truk Lagoon from Operation Hailstone (February, 1944)
Operation Hailstone, conducted on 17–18 February 1944, was a major battle between the United States fast carrier Task Force 58 against the forward operating naval base of the Imperial Japanese Navy at Truk Lagoon (modern-day Chuuk, Federated States of Micronesia). The battle saw devastating losses for the Japanese forces with over 4500 casualties, over 50 ships sunk and over 250 planes lost. Because the battle losses were so skewed, the United St…
Broadscale deep learning model for archaeological feature detection across the Maya area
Documenting the First Three U.S. Aircraft Discovered in Truk Lagoon from Operation Hailstone (February, 1944)
Operation Hailstone, conducted on 17–18 February 1944, was a major battle between the United States fast carrier Task Force 58 against the forward operating naval base of the Imperial Japanese Navy at Truk Lagoon (modern-day Chuuk, Federated States of Micronesia). The battle saw devastating losses for the Japanese forces with over 4500 casualties, over 50 ships sunk and over 250 planes lost. Because the battle losses were so skewed, the United St…
Broadscale deep learning model for archaeological feature detection across the Maya area
Deep Learning for Detection of Underwater Aircraft Wrecks from US Conflicts
There are more than 72,000 missing in action service members from WWII, many of whom were lost at sea in aircraft. Using high-resolution sidescan sonar and a YOLOv7 model, we present a deep learning approach to expedite the search for these individuals. Our training dataset is the largest aircraft wreck-focused dataset that has been published to date, with 19 unique aircraft wrecks, composed of 290 individual fragments and located across six coun…
Aeronautics (2 works) · Archaeological Research and Protection (2 works) · Archaeology (2 works) · Engineering (2 works) · Geography (2 works) · Geology (2 works) · History (2 works) · Oceanography (2 works) · 3D Surveying and Cultural Heritage (1 work) · Artificial Intelligence (1 work)