56 citations · 111 across the 8 of their papers we have counts for
8 papers
SSVOD: Semi-Supervised Video Object Detection with Sparse Annotations
Tanvir Mahmud, Chun-Hao Liu, Burhaneddin Yaman +1
Despite significant progress in semi-supervised learning for image object detection, several key issues are yet to be addressed for video object detection: (1) Achieving good perfo…
Instance-Aware Repeat Factor Sampling for Long-Tailed Object Detection
Burhaneddin Yaman, Tanvir Mahmud, Chun-Hao Liu
We propose an embarrassingly simple method -- instance-aware repeat factor sampling (IRFS) to address the problem of imbalanced data in long-tailed object detection. Imbalanced dat…
CIFF-Net: Contextual Image Feature Fusion for Melanoma Diagnosis
Md Awsafur Rahman, Bishmoy Paul, Tanvir Mahmud +1
Melanoma is considered to be the deadliest variant of skin cancer causing around 75\% of total skin cancer deaths. To diagnose Melanoma, clinicians assess and compare multiple skin…
AVE-CLIP: AudioCLIP-based Multi-window Temporal Transformer for Audio Visual Event Localization
Tanvir Mahmud, Diana Marculescu
An audio-visual event (AVE) is denoted by the correspondence of the visual and auditory signals in a video segment. Precise localization of the AVEs is very challenging since it de…
A Novel Multi-Stage Training Approach for Human Activity Recognition from Multimodal Wearable Sensor Data Using Deep Neural Network
Tanvir Mahmud, A. Q. M. Sazzad Sayyed, Shaikh Anowarul Fattah +1
Deep neural network is an effective choice to automatically recognize human actions utilizing data from various wearable sensors. These networks automate the process of feature ext…
CovTANet: A Hybrid Tri-level Attention Based Network for Lesion Segmentation, Diagnosis, and Severity Prediction of COVID-19 Chest CT Scans
Tanvir Mahmud, Md. Jahin Alam, Sakib Chowdhury +4
Rapid and precise diagnosis of COVID-19 is one of the major challenges faced by the global community to control the spread of this overgrowing pandemic. In this paper, a hybrid neu…
Automatic Diagnosis of Malaria from Thin Blood Smear Images using Deep Convolutional Neural Network with Multi-Resolution Feature Fusion
Tanvir Mahmud, Shaikh Anowarul Fattah
Malaria, a life-threatening disease, infects millions of people every year throughout the world demanding faster diagnosis for proper treatment before any damages occur. In this pa…
CovSegNet: A Multi Encoder-Decoder Architecture for Improved Lesion Segmentation of COVID-19 Chest CT Scans
Tanvir Mahmud, Md Awsafur Rahman, Shaikh Anowarul Fattah +1
Automatic lung lesions segmentation of chest CT scans is considered a pivotal stage towards accurate diagnosis and severity measurement of COVID-19. Traditional U-shaped encoder-de…