49 citations · 152 across the 13 of their papers we have counts for
14 papers
Learning to Generalize towards Unseen Domains via a Content-Aware Style Invariant Model for Disease Detection from Chest X-rays
Mohammad Zunaed, Md. Aynal Haque, Taufiq Hasan
Performance degradation due to distribution discrepancy is a longstanding challenge in intelligent imaging, particularly for chest X-rays (CXRs). Recent studies have demonstrated t…
SpectNet : End-to-End Audio Signal Classification Using Learnable Spectrograms
Md. Istiaq Ansari, Taufiq Hasan
Pattern recognition from audio signals is an active research topic encompassing audio tagging, acoustic scene classification, music classification, and other areas. Spectrogram and…
ThoraX-PriorNet: A Novel Attention-Based Architecture Using Anatomical Prior Probability Maps for Thoracic Disease Classification
Md. Iqbal Hossain, Mohammad Zunaed, Md. Kawsar Ahmed +3
Objective: Computer-aided disease diagnosis and prognosis based on medical images is a rapidly emerging field. Many Convolutional Neural Network (CNN) architectures have been devel…
BON: An extended public domain dataset for human activity recognition
Girmaw Abebe Tadesse, Oliver Bent, Komminist Weldemariam +3
Body-worn first-person vision (FPV) camera enables to extract a rich source of information on the environment from the subject's viewpoint. However, the research progress in wearab…
Heart Sound Classification Considering Additive Noise and Convolutional Distortion
Farhat Binte Azam, Md. Istiaq Ansari, Ian Mclane +1
Cardiac auscultation is an essential point-of-care method used for the early diagnosis of heart diseases. Automatic analysis of heart sounds for abnormality detection is faced with…
Anatomy-XNet: An Anatomy Aware Convolutional Neural Network for Thoracic Disease Classification in Chest X-rays
Uday Kamal, Mohammad Zunaed, Nusrat Binta Nizam +1
Thoracic disease detection from chest radiographs using deep learning methods has been an active area of research in the last decade. Most previous methods attempt to focus on the…
Respiratory Distress Detection from Telephone Speech using Acoustic and Prosodic Features
Meemnur Rashid, Kaisar Ahmed Alman, Khaled Hasan +2
With the widespread use of telemedicine services, automatic assessment of health conditions via telephone speech can significantly impact public health. This work summarizes our pr…
A Lightweight CNN Model for Detecting Respiratory Diseases from Lung Auscultation Sounds using EMD-CWT-based Hybrid Scalogram
Samiul Based Shuvo, Shams Nafisa Ali, Soham Irtiza Swapnil +2
Listening to lung sounds through auscultation is vital in examining the respiratory system for abnormalities. Automated analysis of lung auscultation sounds can be beneficial to th…
SegCodeNet: Color-Coded Segmentation Masks for Activity Detection from Wearable Cameras
Asif Shahriyar Sushmit, Partho Ghosh, Md. Abrar Istiak +3
Activity detection from first-person videos (FPV) captured using a wearable camera is an active research field with potential applications in many sectors, including healthcare, la…
Privacy-Aware Activity Classification from First Person Office Videos
Partho Ghosh, Md. Abrar Istiak, Nayeeb Rashid +5
In the advent of wearable body-cameras, human activity classification from First-Person Videos (FPV) has become a topic of increasing importance for various applications, including…
X-Ray Image Compression Using Convolutional Recurrent Neural Networks
Asif Shahriyar Sushmit, Shakib Uz Zaman, Ahmed Imtiaz Humayun +2
In the advent of a digital health revolution, vast amounts of clinical data are being generated, stored and processed on a daily basis. This has made the storage and retrieval of l…
End-to-end Sleep Staging with Raw Single Channel EEG using Deep Residual ConvNets
Ahmed Imtiaz Humayun, Asif Shahriyar Sushmit, Taufiq Hasan +1
Humans approximately spend a third of their life sleeping, which makes monitoring sleep an integral part of well-being. In this paper, a 34-layer deep residual ConvNet architecture…
Learning Front-end Filter-bank Parameters using Convolutional Neural Networks for Abnormal Heart Sound Detection
Ahmed Imtiaz Humayun, Shabnam Ghaffarzadegan, Zhe Feng +1
Automatic heart sound abnormality detection can play a vital role in the early diagnosis of heart diseases, particularly in low-resource settings. The state-of-the-art algorithms f…
An Ensemble of Transfer, Semi-supervised and Supervised Learning Methods for Pathological Heart Sound Classification
Ahmed Imtiaz Humayun, Md. Tauhiduzzaman Khan, Shabnam Ghaffarzadegan +2
In this work, we propose an ensemble of classifiers to distinguish between various degrees of abnormalities of the heart using Phonocardiogram (PCG) signals acquired using digital…