Tag: Explainable AI

Congratulations to Dr. Matthew Cook for successfully passing his PhD dissertation exam! Dr. Cook’s research centers on developing algorithms that use null space projections within neural networks to add additional functionality. The primary application of this method is detecting out-of-distribution data, such as encountering unexpected objects during Automatic Target Recognition data collections. Moreover, results showed […]

Congratulations to Dr. Spencer Chang for successfully passing his PhD dissertation exam! Dr. Chang’s research demonstrated the potential of combining learnable histogram features with deep learning convolutional methods. Additionally, he delivered key insights into enhancing statistical texture feature learning and explored the nuances of embedding histogram layers to maximize their impact within feature extraction pipelines. […]