Related references
Note: Only part of the references are listed.
Article
Computer Science, Artificial Intelligence
Zhenshan Bing et al.
Summary: The subject of deep reinforcement learning (DRL) has developed rapidly and is now applied in various fields. However, artificial agents trained with RL algorithms require large amounts of training data. The concept of meta-reinforcement learning (meta-RL) enables agents to learn new skills from a small amount of experience. This study introduces a training strategy for non-stationary environments and a task representation based on Gaussian mixture models.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Guillermo Gallego et al.
Summary: This paper provides a comprehensive overview of event-based vision, focusing on the applications and algorithms developed for event cameras. Event cameras differ from traditional cameras in their asynchronous measurement of per-pixel brightness changes, offering high temporal resolution, very high dynamic range, low power consumption, and high pixel bandwidth. The paper discusses techniques for processing events, including learning-based methods and specialized processors. It also highlights the remaining challenges and opportunities in the field of bio-inspired perception and interaction for machines.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Review
Construction & Building Technology
Guoqing Jing et al.
Summary: This paper reviews the recent developments and critical barriers of railway inspection robots, introducing the sensors, methods, and platforms used in railway inspection. It also presents test results of a prototype track inspection robot to analyze the feasibility of railway inspection robots. Furthermore, the current limitations of railway inspection robots are discussed, and future developments are provided.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Computer Science, Artificial Intelligence
Zhenshan Bing et al.
Summary: In this article, a computational HDC network consistent with neurophysiological findings concerning biological HDCs is proposed and implemented in robotic navigation tasks. The network represents the directional heading relying solely on angular velocity input and demonstrates excellent performance in accuracy and real-time capability through extensive simulations and real-world experiments.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Review
Automation & Control Systems
Fan Liu et al.
Summary: This review summarizes the latest research findings and analyzes the developmental trends of driver fatigue detection. Four different fatigue detection technologies based on driver physiological signals, behavior features, vehicle running features, and information fusion are discussed. The applications of RGB-D camera and deep learning are highlighted. Experimental results showed the effectiveness of deep learning in extracting fatigue features.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Green & Sustainable Science & Technology
Yu Zhang et al.
Summary: This paper proposes an improved method for vehicle detection in different traffic scenarios based on an improved YOLO v5 network to reduce the false detection rate caused by occlusion. The proposed method enhances the network's perception of small targets through the Flip-Mosaic algorithm. A multi-type vehicle target dataset collected in different scenarios is used for training the detection model. Experimental results demonstrate that the Flip-Mosaic data enhancement algorithm can improve the accuracy of vehicle detection and reduce the false detection rate.
Review
Chemistry, Analytical
Susrutha Babu Sukhavasi et al.
Summary: Recent advancements in CMOS image sensors have allowed for their usage in various surveillance fields, such as visual surveillance, aerial surveillance, environmental monitoring by satellites, agricultural monitoring, and driver assistance in the automotive industry. This paper provides an overview of CMOS image sensor-based surveillance applications over the past decade, detailing design characteristics and surveying different models used in each application.
Article
Computer Science, Artificial Intelligence
Henri Rebecq et al.
Summary: Event cameras are sensors that report brightness changes in the form of asynchronous events, offering advantages such as high temporal resolution, dynamic range, and lack of motion blur. This study introduces a data-driven approach to reconstruct intensity images from event streams, showcasing significant improvements in terms of image quality and real-time performance compared to existing methods.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2021)
Article
Computer Science, Artificial Intelligence
Pablo Rodrigo Gantier Cadena et al.
Summary: Event-based cameras offer advantages over traditional cameras, but utilizing the data they produce is challenging due to the unique nature of event sensors. Neural networks have led to significant advances in event-based image reconstruction, with the new SPA DE-E2VID model showing improved video quality. The model also features faster training time and allows reconstruction without a temporal loss function, demonstrating promising results for event camera technology.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2021)
Article
Computer Science, Artificial Intelligence
Jingru Yi et al.
COMPUTER VISION AND IMAGE UNDERSTANDING
(2019)
Article
Computer Science, Information Systems
George K. Adam et al.
Article
Computer Science, Artificial Intelligence
Gottfried Munda et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2018)
Article
Robotics
Antoni Rosinol Vidal et al.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2018)
Article
Computer Science, Artificial Intelligence
Olga Russakovsky et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2015)
Article
Neurosciences
Garrick Orchard et al.
Frontiers in Neuroscience
(2015)
Article
Engineering, Electrical & Electronic
Christoph Posch et al.
PROCEEDINGS OF THE IEEE
(2014)
Article
Engineering, Electrical & Electronic
Christoph Posch et al.
IEEE JOURNAL OF SOLID-STATE CIRCUITS
(2011)
Article
Computer Science, Artificial Intelligence
Z Wang et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2004)