Uformer: A UNet-Transformer fused robust end-to-end deep learning framework for real-time denoising of lung sounds

no code implementations • 5 Apr 2024 • Samiul Based Shuvo, Syed Samiul Alam, Taufiq Hasan

The proposed model showed an average SNR improvement of 16. 51 dB when evaluated with -12 dB LS signals.

Denoising

Benchmarking Deep Learning Frameworks for Automated Diagnosis of Ocular Toxoplasmosis: A Comprehensive Approach to Classification and Segmentation

no code implementations • 18 May 2023 • Syed Samiul Alam, Samiul Based Shuvo, Shams Nafisa Ali, Fardeen Ahmed, Arbil Chakma, Yeong Min Jang

We have performed in-depth analysis of different feature extraction techniques in order to find the most optimal one for OT classification and segmentation of lesions.

Benchmarking Transfer Learning

NRC-Net: Automated noise robust cardio net for detecting valvular cardiac diseases using optimum transformation method with heart sound signals

no code implementations • 29 Apr 2023 • Samiul Based Shuvo, Syed Samiul Alam, Syeda Umme Ayman, Arbil Chakma, Prabal Datta Barua, U Rajendra Acharya

Therefore, this study aims to discover the optimal transformation method for detecting CVDs using noisy heart sound signals and propose a noise robust network to improve the CVDs classification performance. For the identification of the optimal transformation method for noisy heart sound data mel-frequency cepstral coefficients (MFCCs), short-time Fourier transform (STFT), constant-Q nonstationary Gabor transform (CQT) and continuous wavelet transform (CWT) has been used with VGG16.