351 citations · 408 across the 11 of their papers we have counts for
8 papers · 1 filter
Unsupervised Domain Adaptation in Person re-ID via k-Reciprocal Clustering and Large-Scale Heterogeneous Environment Synthesis
Devinder Kumar, Parthipan Siva, Paul Marchwica +1
An ongoing major challenge in computer vision is the task of person re-identification, where the goal is to match individuals across different, non-overlapping camera views. While…
Fairest of Them All: Establishing a Strong Baseline for Cross-Domain Person ReID
Devinder Kumar, Parthipan Siva, Paul Marchwica +1
Person re-identification (ReID) remains a very difficult challenge in computer vision, and critical for large-scale video surveillance scenarios where an individual could appear in…
SISC: End-to-end Interpretable Discovery Radiomics-Driven Lung Cancer Prediction via Stacked Interpretable Sequencing Cells
Vignesh Sankar, Devinder Kumar, David A. Clausi +2
Objective: Lung cancer is the leading cause of cancer-related death worldwide. Computer-aided diagnosis (CAD) systems have shown significant promise in recent years for facilitatin…
Explaining the Unexplained: A CLass-Enhanced Attentive Response (CLEAR) Approach to Understanding Deep Neural Networks
Devinder Kumar, Alexander Wong, Graham W. Taylor
In this work, we propose CLass-Enhanced Attentive Response (CLEAR): an approach to visualize and understand the decisions made by deep neural networks (DNNs) given a specific input…
Understanding Anatomy Classification Through Attentive Response Maps
Devinder Kumar, Vlado Menkovski, Graham W. Taylor +1
One of the main challenges for broad adoption of deep learning based models such as convolutional neural networks (CNN), is the lack of understanding of their decisions. In many ap…
Discovery Radiomics via StochasticNet Sequencers for Cancer Detection
Mohammad Javad Shafiee, Audrey G. Chung, Devinder Kumar +3
Radiomics has proven to be a powerful prognostic tool for cancer detection, and has previously been applied in lung, breast, prostate, and head-and-neck cancer studies with great s…