Research Interests

Machine Learning, Deep Learning, Texture Analysis, Pattern Recognition, Computer Vision, Image Processing


Dr. Peeples has developed and refined novel deep learning methods for texture characterization, segmentation, and classification of images. His current research seeks to extend this work (e.g., other data modalities, multi-scale analysis) and explore new aspects such as developing algorithms for explainable artificial intelligence and various real-world applications in several domains (e.g., biomedical, agriculture). These methods can then be applied toward automated image understanding, object detection, and classification. Learn more about our sponsored research projects here.

Current Research Projects

Multi‑modal, Multi‑task Data Analysis for Automated Plant Phenotyping

Histogram Layers for Improved Target Classification

Neural Handcrafted Features

Past Research Projects

Seafloor Segmentation for Office of Naval Research

Histological Image Segmentation

Sesame Root Architecture Analysis

Bias in Machine Learning