19 citations · 46 across the 7 of their papers we have counts for
7 papers
Polar Separable Transform for Efficient Orthogonal Rotation-Invariant Image Representation
Satya P. Singh, Rashmi Chaudhry, Anand Srivastava +1
Orthogonal moment-based image representations are fundamental in computer vision, but classical methods suffer from high computational complexity and numerical instability at large…
Improving Speech Emotion Recognition with Mutual Information Regularized Generative Model
Chung-Soo Ahn, Rajib Rana, Sunil Sivadas +2
Lack of large, well-annotated emotional speech corpora continues to limit the performance and robustness of speech emotion recognition (SER), particularly as models grow more compl…
Subcortical Masks Generation in CT Images via Ensemble-Based Cross-Domain Label Transfer
Augustine X. W. Lee, Pak-Hei Yeung, Jagath C. Rajapakse
Subcortical segmentation in neuroimages plays an important role in understanding brain anatomy and facilitating computer-aided diagnosis of traumatic brain injuries and neurodegene…
Pharmacophore-guided de novo drug design with diffusion bridge
Conghao Wang, Jagath C. Rajapakse
De novo design of bioactive drug molecules with potential to treat desired biological targets is a profound task in the drug discovery process. Existing approaches tend to leverage…
Deep Fourier-embedded Network for RGB and Thermal Salient Object Detection
Pengfei Lyu, Xiaosheng Yu, Pak-Hei Yeung +2
The rapid development of deep learning has significantly improved salient object detection (SOD) combining both RGB and thermal (RGB-T) images. However, existing Transformer-based…
Efficient Fourier Filtering Network with Contrastive Learning for AAV-based Unaligned Bimodal Salient Object Detection
Pengfei Lyu, Pak-Hei Yeung, Xiaosheng Yu +3
Autonomous aerial vehicle (AAV)-based bi-modal salient object detection (BSOD) aims to segment salient objects in a scene utilizing complementary cues in unaligned RGB and thermal…
Discovering robust biomarkers of psychiatric disorders from resting-state functional MRI via graph neural networks: A systematic review
Yi Hao Chan, Deepank Girish, Sukrit Gupta +5
Graph neural networks (GNN) have emerged as a popular tool for modelling functional magnetic resonance imaging (fMRI) datasets. Many recent studies have reported significant improv…