7 citations · 12 across the 6 of their papers we have counts for
8 papers
End-to-End Unmixing with Material Prompts for Hyperspectral Object Tracking
Xu Han, Mohammad Aminul Islam, Lei Wang +5
Hyperspectral imagery encodes rich material properties that can improve tracking robustness under appearance ambiguity, illumination change, and background clutter. However, due to…
Hy-Tracker: A Novel Framework for Enhancing Efficiency and Accuracy of Object Tracking in Hyperspectral Videos
Mohammad Aminul Islam, Wangzhi Xing, Jun Zhou +2
Hyperspectral object tracking has recently emerged as a topic of great interest in the remote sensing community. The hyperspectral image, with its many bands, provides a rich sourc…
Deep Learning-Based Single-Ended Objective Quality Measures for Time-Scale Modified Audio
Timothy Roberts, Aaron Nicolson, Kuldip K. Paliwal
Objective evaluation of audio processed with Time-Scale Modification (TSM) is seeing a resurgence of interest. Recently, a labelled time-scaled audio dataset was used to train an o…
A time-scale modification dataset with subjective quality labels
Timothy Roberts, Kuldip K. Paliwal
Time Scale Modification (TSM) is a well-researched field; however, no effective objective measure of quality exists. This paper details the creation, subjective evaluation, and ana…
An Objective Measure of Quality for Time-Scale Modification of Audio
Timothy Roberts, Kuldip K. Paliwal
Objective evaluation of audio processed with Time-Scale Modification (TSM) remains an open problem. Recently, a dataset of time-scaled audio with subjective quality labels was publ…
Deep Residual-Dense Lattice Network for Speech Enhancement
Mohammad Nikzad, Aaron Nicolson, Yongsheng Gao +3
Convolutional neural networks (CNNs) with residual links (ResNets) and causal dilated convolutional units have been the network of choice for deep learning approaches to speech enh…
Sum-Product Networks for Robust Automatic Speaker Identification
Aaron Nicolson, Kuldip K. Paliwal
We introduce sum-product networks (SPNs) for robust speech processing through a simple robust automatic speaker identification (ASI) task. SPNs are deep probabilistic graphical mod…
Deep Xi as a Front-End for Robust Automatic Speech Recognition
Aaron Nicolson, Kuldip K. Paliwal
Current front-ends for robust automatic speech recognition(ASR) include masking- and mapping-based deep learning approaches to speech enhancement. A recently proposed deep learning…