Abstract Automated Foreign Object Debris (FOD) detection offers significant benefit to the
aviation industry by reducing human error and enabling continuous surveillance. This paper …

Contrastive self-supervised learning has recently benefited fMRI classification with inductive
biases. Its weak label reliance prevents overfitting on small medical datasets and tackles the …

Visual representation for fine-grained visual recognition can be learned by mandatorily
enforcing all samples of the same category into a uniform representation. This strict training …

Modern earth observation sensors have revolutionized the remote sensing community by
improving remote sensing image quality. However, Pixel-based image analysis methods …

This study aims to capture subtle changes in the pupil, identify relatively weak inter-class
changes, extract more abstract and discriminative pupil features, and study a pupil …

Extracting spectral-spatial features from Hyperspectral imagery (HSI) has been proven to be
efficient for classification tasks. A recently developed superpixelwised PCA (SuperPCA) …

Different from large-scale classification tasks, fine-grained visual classification is a
challenging task due to two critical problems: 1) evident intra-class variances and subtle …

Earthworks such as earthen berms have been constructed across the western US since the
late 1800s to mitigate erosion in landscapes where water is both the dominant driver of …

Data-free knowledge distillation transfers knowledge by recovering training data from a pre-
trained model. Despite the recent success of seeking global data diversity, the diversity …

Gait recognition has become an important biometric feature for human identification, in
addition to data such as face, iris, and fingerprint. The goal of human gait recognition is to …