4 citations · 9 across the 6 of their papers we have counts for
6 papers
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…
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…