4,024 research outputs found
Artificial Intelligence and Machine Learning: A Perspective on Integrated Systems Opportunities and Challenges for Multi-Domain Operations
This paper provides a perspective on historical background, innovation and applications of Artificial Intelligence (AI)
and Machine Learning (ML), data successes and systems challenges, national security interests, and mission
opportunities for system problems. AI and ML today are used interchangeably, or together as AI/ML, and are ubiquitous
among many industries and applications. The recent explosion, based on a confluence of new ML algorithms, large data
sets, and fast and cheap computing, has demonstrated impressive results in classification and regression and used for
prediction, and decision-making. Yet, AI/ML today lacks a precise definition, and as a technical discipline, it has grown
beyond its origins in computer science. Even though there are impressive feats, primarily of ML, there still is much work
needed in order to see the systems benefits of AI, such as perception, reasoning, planning, acting, learning,
communicating, and abstraction. Recent national security interests in AI/ML have focused on problems including multidomain operations (MDO), and this has renewed the focus on a systems view of AI/ML. This paper will address the
solutions for systems from an AI/ML perspective and that these solutions will draw from methods in AI and ML, as well
as computational methods in control, estimation, communication, and information theory, as in the early days of
cybernetics. Along with the focus on developing technology, this paper will also address the challenges of integrating
these AI/ML systems for warfare
Manipulation Detection in Satellite Images Using Deep Belief Networks
Satellite images are more accessible with the increase of commercial
satellites being orbited. These images are used in a wide range of applications
including agricultural management, meteorological prediction, damage assessment
from natural disasters, and cartography. Image manipulation tools including
both manual editing tools and automated techniques can be easily used to tamper
and modify satellite imagery. One type of manipulation that we examine in this
paper is the splice attack where a region from one image (or the same image) is
inserted (spliced) into an image. In this paper, we present a one-class
detection method based on deep belief networks (DBN) for splicing detection and
localization without using any prior knowledge of the manipulations. We
evaluate the performance of our approach and show that it provides good
detection and localization accuracies in small forgeries compared to other
approaches
Ono: an open platform for social robotics
In recent times, the focal point of research in robotics has shifted from industrial ro- bots toward robots that interact with humans in an intuitive and safe manner. This evolution has resulted in the subfield of social robotics, which pertains to robots that function in a human environment and that can communicate with humans in an int- uitive way, e.g. with facial expressions. Social robots have the potential to impact many different aspects of our lives, but one particularly promising application is the use of robots in therapy, such as the treatment of children with autism. Unfortunately, many of the existing social robots are neither suited for practical use in therapy nor for large scale studies, mainly because they are expensive, one-of-a-kind robots that are hard to modify to suit a specific need. We created Ono, a social robotics platform, to tackle these issues. Ono is composed entirely from off-the-shelf components and cheap materials, and can be built at a local FabLab at the fraction of the cost of other robots. Ono is also entirely open source and the modular design further encourages modification and reuse of parts of the platform
- …