All Outputs (3)

Review of the AI-Based Analysis of Abdominal Organs from Routine CT Scans (2025)
Journal Article
Tavakolian, N., Nazemi, A., & Suen, C. Y. (2025). Review of the AI-Based Analysis of Abdominal Organs from Routine CT Scans. Applied Sciences, 15(5), Article 2516. https://doi.org/10.3390/app15052516

Accurate and timely segmentation of liver trauma in computed tomography (CT) images is essential for effective diagnosis and management in emergency medicine. This review examines advancements in liver segmentation techniques from 1993 to 2024, focus... Read More about Review of the AI-Based Analysis of Abdominal Organs from Routine CT Scans.

Iterative Speech Enhancement with Transformers (2024)
Presentation / Conference Contribution
Nazemi, A., Sami, A., Sami, M., & Hussain, A. (2024, September). Iterative Speech Enhancement with Transformers. Presented at 3rd COG-MHEAR Workshop on Audio-Visual Speech Enhancement (AVSEC), Kos, Greece

Enhancing audio quality in audio-video speech enhancement (AVSE) is a crucial step in improving the performance of speech recognition systems, particularly by integrating visual and auditory data to create more robust and accurate models. This study... Read More about Iterative Speech Enhancement with Transformers.

A Framework for Speech Enhancement based on Audio Signal and Speaker Embeddings (2024)
Presentation / Conference Contribution
Nazemi, A., Sami, A., Sami, M., & Hussain, A. (2024, September). A Framework for Speech Enhancement based on Audio Signal and Speaker Embeddings. Presented at 3rd COG-MHEAR Workshop on Audio-Visual Speech Enhancement (AVSEC), Kos Island, Greece

This study addresses the challenge of speech enhancement within an audio-only context. Our proposed framework extracts speaker embeddings and voice signals, subsequently integrating these components to synthesise a voice based on the extracted data.... Read More about A Framework for Speech Enhancement based on Audio Signal and Speaker Embeddings.