no code implementations • 15 May 2024 • Farnaz Khun Jush, Steffen Vogler, Tuan Truong, Matthias Lenga
While content-based image retrieval (CBIR) has been extensively studied in natural image retrieval, its application to medical images presents ongoing challenges, primarily due to the 3D nature of medical images.
no code implementations • 14 May 2024 • Melanie Dohmen, Mark Klemens, Ivo Baltruschat, Tuan Truong, Matthias Lenga
In this study, we give an overview of reference and non-reference metrics for image synthesis assessment and investigate the ability of nine metrics, that need a reference (SSIM, MS-SSIM, PSNR, MSE, NMSE, MAE, LPIPS, NMI and PCC) and three non-reference metrics (BLUR, MSN, MNG) to detect 11 kinds of distortions in MR images from the BraSyn dataset.
no code implementations • 12 Dec 2023 • Tuan Truong, Farnaz Khun Jush, Matthias Lenga
Near- and duplicate image detection is a critical concern in the field of medical imaging.
no code implementations • 22 Nov 2023 • Farnaz Khun Jush, Tuan Truong, Steffen Vogler, Matthias Lenga
A wide range of imaging techniques and data formats available for medical images make accurate retrieval from image databases challenging.
no code implementations • 29 Sep 2023 • Tuan Truong, Hoang-Phi Nguyen, Tung Pham, Minh-Tuan Tran, Mehrtash Harandi, Dinh Phung, Trung Le
Motivated by this analysis, we introduce our algorithm, Riemannian Sharpness-Aware Minimization (RSAM).
1 code implementation • 20 May 2023 • Jia Qi Yip, Tuan Truong, Dianwen Ng, Chong Zhang, Yukun Ma, Trung Hieu Nguyen, Chongjia Ni, Shengkui Zhao, Eng Siong Chng, Bin Ma
In this paper, we propose ACA-Net, a lightweight, global context-aware speaker embedding extractor for Speaker Verification (SV) that improves upon existing work by using Asymmetric Cross Attention (ACA) to replace temporal pooling.
1 code implementation • 22 Nov 2022 • Chris Cameron, Jason Hartford, Taylor Lundy, Tuan Truong, Alan Milligan, Rex Chen, Kevin Leyton-Brown
We introduce Monte Carlo Forest Search (MCFS), a class of reinforcement learning (RL) algorithms for learning policies in {tree MDPs}, for which policy execution involves traversing an exponential-sized tree.
no code implementations • 22 Apr 2022 • Tuan Truong, Matthias Lenga, Antoine Serrurier, Sadegh Mohammadi
Our findings show that the use of self-attention to combine extracted features from cough, breath, and speech sounds leads to the best performance with an Area Under the Receiver Operating Characteristic Curve (AUC) score of 0. 8658, a sensitivity of 0. 8057, and a specificity of 0. 7958.
no code implementations • 23 Aug 2021 • Tuan Truong, Sadegh Mohammadi, Matthias Lenga
In addition, we introduce Dynamic Visual Meta-Embedding (DVME) as an end-to-end transfer learning approach that fuses pretrained embeddings from multiple models.