4 citations · 10 across the 8 of their papers we have counts for
10 papers
FlowLOT: Linearized Optimal Transport for Flow Cytometry Analysis
Naqib Sad Pathan, Mohammad Shifat-E-Rabbi, Kristofor E. Pas +3
Multiparameter flow cytometry generates high-dimensional, unordered single-cell mea- surement data for disease diagnosis and monitoring, yet analysis often remains dependent on man…
Linear optimal transport subspaces for point set classification
Mohammad Shifat E Rabbi, Naqib Sad Pathan, Shiying Li +3
Learning from point sets is an essential component in many computer vision and machine learning applications. Native, unordered, and permutation invariant set structure space is ch…
The Radon Signed Cumulative Distribution Transform and its applications in classification of Signed Images
Le Gong, Shiying Li, Naqib Sad Pathan +4
Here we describe a new image representation technique based on the mathematics of transport and optimal transport. The method relies on the combination of the well-known Radon tran…
A sliced-Wasserstein distance-based approach for out-of-class-distribution detection
Mohammad Shifat E Rabbi, Abu Hasnat Mohammad Rubaiyat, Yan Zhuang +1
There exist growing interests in intelligent systems for numerous medical imaging, image processing, and computer vision applications, such as face recognition, medical diagnosis,…
End-to-End Signal Classification in Signed Cumulative Distribution Transform Space
Abu Hasnat Mohammad Rubaiyat, Shiying Li, Xuwang Yin +3
This paper presents a new end-to-end signal classification method using the signed cumulative distribution transform (SCDT). We adopt a transport-based generative model to define t…
Local Sliced-Wasserstein Feature Sets for Illumination-invariant Face Recognition
Yan Zhuang, Shiying Li, Mohammad Shifat-E-Rabbi +3
We present a new method for face recognition from digital images acquired under varying illumination conditions. The method is based on mathematical modeling of local gradient dist…
Invariance encoding in sliced-Wasserstein space for image classification with limited training data
Mohammad Shifat E Rabbi, Yan Zhuang, Shiying Li +3
Deep convolutional neural networks (CNNs) are broadly considered to be state-of-the-art generic end-to-end image classification systems. However, they are known to underperform whe…
Nearest Subspace Search in The Signed Cumulative Distribution Transform Space for 1D Signal Classification
Abu Hasnat Mohammad Rubaiyat, Mohammad Shifat-E-Rabbi, Yan Zhuang +2
This paper presents a new method to classify 1D signals using the signed cumulative distribution transform (SCDT). The proposed method exploits certain linearization properties of…
Radon cumulative distribution transform subspace modeling for image classification
Mohammad Shifat-E-Rabbi, Xuwang Yin, Abu Hasnat Mohammad Rubaiyat +5
We present a new supervised image classification method applicable to a broad class of image deformation models. The method makes use of the previously described Radon Cumulative D…
Cell image classification: a comparative overview
Mohammad Shifat-E-Rabbi, Xuwang Yin, Cailey Elizabeth Fitzgerald +1
Cell image classification methods are currently being used in numerous applications in cell biology and medicine. Applications include understanding the effects of genes and drugs…