Software & Downloads

APL is the owner of many original works of authorship that are protected by copyright—the intangible property right granted by federal statute for an original work fixed in a tangible medium. The following samples provide an in-depth view of available works and are taken from the Laboratory's hundreds of copyrighted materials available for license.

Contact us at the Office of Technology Transfer for more information and to obtain permission to exercise one or more of the rights under copyright, including the right to reproduce, prepare derivative works, distribute by sale or otherwise, perform, and/or display publicly.


This research system enables simplified dynamic access to unrelated data sources through the Internet.

Connectome Analysis through Joint Annotation of Large 3D Data (CAJAL3D) Application Programming Interface (API) and Images to Graphs Pipeline

The CAJAL3D API is designed to facilitate the large-scale, multi-institution collaboration required to reverse-engineer significant quantities of cortical tissue. The images-to-graphs pipeline provides the first fully automated method to build and assess brain graphs.

Cloud Computing 101: A Primer for Project Managers

Link to an Amazon-published book by an APL author on Cloud Computing for helping Project Managers and other non-technical staff better understand Cloud Computing.


Elgg is an open-source framework for building social networking Web sites.

Feature Selection Methods for Zero-Shot Learning of Neural Activity

This MATLAB code may be used to replicate the results published in the manuscript [Ref 1], building zero-shot prediction models to classify previously unseen stimulus through neural signals and semantic attributes. The code incorporates feature extraction, feature selection, training and testing through Leave-One-Class-Out cross-validation, and the analysis of the results concentrating on the feature selection variations. For more information, please refer to [Ref 2].

Material for Courses and Tutorials in Model-Based Systems Engineering

Model-based systems engineering is the formalized application of modeling to support system requirements, design, analysis, verification, and validation activities beginning in the conceptual design phase and continuing throughout development and later life-cycle phases.

Net Taster

NetTaster is an intrusion detection system that correlates real-time network traffic content and node activity in order to detect attacks on a network.

Passive Forensic Identification of Network TCP/IP Communication Endpoints

This passive network system identifies specific machines through remote network fingerprinting.

Signature Classification Development System

This system offers point-and-click programming for automated image/signal analysis and classification for large quantities of data.

Small Fixed-Wing UAS State Estimation Examples (SUAS Code)

SUAS Code is a set of heavily commented MATLAB® routines that provide example methods for performing state estimation (i.e., position and orientation) of a fixed-wing unmanned aircraft system (UAS) using GPS, gyros, accelerometers, and a magnetometer as sensors. The code is meant as a companion to the Johns Hopkins Technical Digest article "Fundamentals of Small Unmanned Aircraft Flight."