Visually Adaptive Neural Networks for Integrated Synthetic Holographic (VANISH)
Open Access DepositedTechnological advancements on the modern battlefield are driving renewed focus for the development and implementation of advanced camouflage techniques to increase the survivability of both manned and unmanned military platforms. The ongoing development of computer vision-aided detection systems and autonomous combatants requires a new approach to camouflage that provides both qualitative and quantitative enhancements beyond traditional static methods (Kim, 2018). This Praxis explores the concept of blending artificial intelligence (AI) and machine learning (ML) algorithms with photonic smart-skin technologies to create a Visually Adaptive Neural-Network for Integrated Synthetic Holographic (VANISH) applications. This research aims to enhance battlefield stealth by leveraging AI/ML techniques to camouflage troops and their associated equipment in real-time. Much as moviegoers witnessed in John McTiernan’s 1987 film “Predator”, VANISH proposes developing and testing a dynamically adaptive camouflage “smart skin” that responds to visual changes in the environment (Wikipedia, 2024).If operationalized, VANISH technology may address the limitations of static camouflage by incorporating AI/ML adaptability. Traditional camouflaging techniques rely on pre-designed patterns that may not be effective in varying environments, as may be found in urban-based conflicts (Brimley, 2014). This Praxis proposes using deep learning algorithms to continuously analyze the surrounding environments and generate synthetic patterns that seamlessly blend with the background. This real-time adaptability is crucial in modern all-domain combat scenarios where the environments and fighting conditions can shift rapidly. The deliberate use of a wide range of AI/ML libraries and techniques was researched and chosen to allow VANISH to scale across different levels of complexity, from simple color matching applications to sophisticated projections. This scalability would ensure the system can be deployed in various operational contexts, from reconnaissance missions to full-scale combat scenarios. As military operations become increasingly more complex, the ability to integrate and operationalize sophisticated AI/ML applications will undoubtedly play a pivotal role in maintaining strategic advantages over sophisticated adversaries (Scharre, 2018). In conjunction with AI/ML applications, the VANISH Praxis also explores the emerging world of flexible smart skin materials and their potential role in delivering the rendered camouflage outputs from the VANISH baseline code onto a military platform. These smart skins serve as the optical interface between the end user and the VANISH codebase and play a pivotal role in demonstrating the tactical intersection between advanced AI/ML technologies and the all-domain war fighter. As the scrutiny of AI/ML applications grows in the defense sector, this Praxis also explores the critical ethical and legal considerations around this capability. As adaptive camouflage technologies like VANISH advance, concerns around their use in deception, the escalation of conflicts, and the potential for misuse in non-military contexts are sure to arise (Lin, 2019). This Praxis concludes by making recommendations for future areas of research that bridge the gap between electro-optic (EO), infrared (IR), and radio frequency (RF) methods of camouflage to create a single unified solution based on the VANISH baseline.
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