Simple Object Classification Using Binary Data

Binary, or one-bit, representations of data arise naturally in many applications, and are appealing in both hardware implementations and algorithm design. In this work, we study the problem of data classification from binary data and propose a framework with low computation and resource costs. We illustrate the utility of the proposed approach through stylized and realistic numerical experiments, including military classification problems like facial and object recognition. We hope that our framework will serve as a foundation for studying similar types of approaches.