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01/14/2020
Unsupervised Domain Adaptation in Person re-ID via k-Reciprocal Clustering and Large-Scale Heterogeneous Environment Synthesis
An ongoing major challenge in computer vision is the task of person re-i...
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07/28/2019
Fairest of Them All: Establishing a Strong Baseline for Cross-Domain Person ReID
Person re-identification (ReID) remains a very difficult challenge in co...
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04/21/2019
Beyond Explainability: Leveraging Interpretability for Improved Adversarial Learning
In this study, we propose the leveraging of interpretability for tasks b...
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01/15/2019
SISC: End-to-end Interpretable Discovery Radiomics-Driven Lung Cancer Prediction via Stacked Interpretable Sequencing Cells
Objective: Lung cancer is the leading cause of cancer-related death worl...
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10/29/2017
Discovery Radiomics with CLEAR-DR: Interpretable Computer Aided Diagnosis of Diabetic Retinopathy
Objective: Radiomics-driven Computer Aided Diagnosis (CAD) has shown con...
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09/05/2017
Opening the Black Box of Financial AI with CLEAR-Trade: A CLass-Enhanced Attentive Response Approach for Explaining and Visualizing Deep Learning-Driven Stock Market Prediction
Deep learning has been shown to outperform traditional machine learning ...
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04/13/2017
Explaining the Unexplained: A CLass-Enhanced Attentive Response (CLEAR) Approach to Understanding Deep Neural Networks
In this work, we propose CLass-Enhanced Attentive Response (CLEAR): an a...
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11/19/2016
Understanding Anatomy Classification Through Visualization
One of the main challenges for broad adoption of deep convolutional neur...
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11/11/2015
Discovery Radiomics via StochasticNet Sequencers for Cancer Detection
Radiomics has proven to be a powerful prognostic tool for cancer detecti...
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09/01/2015
Discovery Radiomics for Pathologically-Proven Computed Tomography Lung Cancer Prediction
Lung cancer is the leading cause for cancer related deaths. As such, the...
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09/01/2015
