HAMIDREZA FARHADI TOLIE's Outputs (3)

Protecting visual data privacy in offshore industry via underwater image inpainting. (2024)
Presentation / Conference Contribution
TOLIE, H.F., REN, J., CHEN, R. and ZHAO, H. 2024. Protecting visual data privacy in offshore industry via underwater image inpainting. In Proceedings of the 9th International conference on image, vision and computing 2024 (ICIVC 2024), 15-17 July 2024, Suzhou, China. Piscataway: IEEE [online], pages 281-286. Available from: https://doi.org/10.1109/ICIVC61627.2024.10837433

Leveraging advanced artificial intelligence (AI) methodologies offers the advantage of incorporating multiple expert viewpoints, thereby facilitating a more comprehensive inspection of underwater infrastructure. However, the implementation of AI tech... Read More about Protecting visual data privacy in offshore industry via underwater image inpainting..

Enhancing underwater situational awareness: RealSense camera integration with deep learning for improved depth perception and distance measurement. (2024)
Presentation / Conference Contribution
TOLIE, H.F., REN, J., HASAN, M.J. and KANNAN, S. 2024. Enhancing underwater situational awareness: RealSense camera integration with deep learning for improved depth perception and distance measurement. In Bouma, H., Prabhu, R., Yitzhaky, Y. and Kuijf, H.J. (eds.) Artificial intelligence for security and defence applications II: proceedings of the 2024 SPIE Security + defence, 16-20 September 2024, Edinburgh, UK. Proceedings of SPIE, 13206. Bellingham, WA; SPIE [online], paper 1320605. Available from: https://doi.org/10.1117/12.3030972

This work presents a depth image refinement technique designed to enhance the usability of a commercial camera in underwater environments. Stereo vision-based depth cameras offer dense data that is well-suited for accurate environmental understanding... Read More about Enhancing underwater situational awareness: RealSense camera integration with deep learning for improved depth perception and distance measurement..

Promptable sonar image segmentation for distance measurement using SAM. (2024)
Presentation / Conference Contribution
TOLIE, H.F., REN, J., HASAN, M.J., KANNAN, S. and FOUGH, N. 2024. Promptable sonar image segmentation for distance measurement using SAM. In Proceedings of the 2024 IEEE (Institute of Electrical and Electronics Engineers) International workshop on Metrology for the sea; learning to measure sea health parameters (IEEE MetroSea 2024), 14-16 October 2024, Portorose, Slovenia. Piscataway: IEEE [online], pages 229-233. Available from: https://doi.org/10.1109/metrosea62823.2024.10765703

The subsea environment presents numerous challenges for robotic vision, including non-uniform light attenuation, backscattering, floating particles, and low-light conditions, which significantly degrade underwater images. This degradation impacts rob... Read More about Promptable sonar image segmentation for distance measurement using SAM..