Defining materials using laser signals from long distance via deep learning by Nevzat Olgun, İbrahim Türkoğlu

“…Material identification is useful in robotics, industrial manufacturing, autonomous driving and so on. Cameras are generally used in material identification studies. …”
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Calibration Method of the Monocular Omnidirectional Stereo Camera by Ryota Kawamata, Keiichi Betsui, Kazuyoshi Yamazaki, Rei Sakakibara, Takeshi Shimano

“…Compact and low-cost devices are needed for autonomous driving to image and measure distances to objects 360-degree around. …”
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Panoptic SwiftNet: Pyramidal Fusion for Real-Time Panoptic Segmentation by Josip Šarić, Marin Oršić, Siniša Šegvić

“…Dense panoptic prediction is a key ingredient in many existing applications such as autonomous driving, automated warehouses, or remote sensing. …”
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Implementation of a Potential Field-Based Decision-Making Algorithm on Autonomous Vehicles for Driving in Complex Environments by Carlos Martínez, Felipe Jiménez

“…Autonomous driving is undergoing huge developments nowadays. …”
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Recursive Least Squares Based Refinement Network for Vehicle Trajectory Prediction by Shengyi Li, Qifan Xue, Dongfeng Shi, Xuanpeng Li, Weigong Zhang

“…Trajectory prediction of surrounding objects plays a pivotal role in the field of autonomous driving vehicles. In the current rollout process, it suffers from an accumulation of errors, which has a negative impact on prediction accuracy. …”
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Localization based on TDoA projection for autonomous vehicles in 6G cellular networks by Sekchin Chang

“…6G cellular networks are expected to support a full service for autonomous driving. A super-resolution localization is required for the full service. …”
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Lane Mark Detection with Pre-Aligned Spatial-Temporal Attention by Yiman Chen, Zhiyu Xiang

“…Lane mark detection plays an important role in autonomous driving under structural environments. Many deep learning-based lane mark detection methods have been put forward in recent years. …”
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Statistical Modeling of Cultural Differences in Adopting Autonomous Vehicles by Yongdeok Yun, Hyungseok Oh, Rohae Myung

“…As autonomous driving technology develops, the advantages and disadvantages of autonomous vehicles emerge. …”
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Human-like Decision Making for Autonomous Vehicles at the Intersection Using Inverse Reinforcement Learning by Zheng Wu, Fangbing Qu, Lin Yang, Jianwei Gong

“…With the rapid development of autonomous driving technology, both self-driven and human-driven vehicles will share roads in the future and complex information exchange among vehicles will be required. …”
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HAP-Assisted RSMA-Enabled Vehicular Edge Computing: A DRL-Based Optimization Framework by Tri-Hai Nguyen, Laihyuk Park

“…In recent years, the demand for vehicular edge computing (VEC) has grown rapidly due to the increasing need for low-latency and high-throughput applications such as autonomous driving and smart transportation systems. Nevertheless, offering VEC services in rural locations remains a difficulty owing to a lack of network facilities. …”
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RSS Model Improvement Considering Road Conditions for the Application of a Variable Focus Function Camera by Min Joong Kim, Young Min Kim

“…Recently, as the supply of vehicles with autonomous driving functions increases, the safety of vehicles is also an emerging issue. …”
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Multiagent Manuvering with the Use of Reinforcement Learning by Mateusz Orłowski, Paweł Skruch

“…This paper presents an approach for defining, solving, and implementing dynamic cooperative maneuver problems in autonomous driving applications. The formulation of these problems considers a set of cooperating cars as part of a multiagent system. …”
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Smart Parking Lot Based on Edge Cluster Computing for Full Self-Driving Vehicles by Woojae Kim, Inbum Jung

“…One promising area that can be serviced by edge computing in real-time is autonomous driving. Fully self-driving vehicles can operate on roads and in buildings, such as indoor parking lots, using various sensors and communication modules. …”
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Hardware-in-the-Loop Simulation of Self-Driving Electric Vehicles by Dynamic Path Planning and Model Predictive Control by Yi Chung, Yee-Pien Yang

“…Both manual and autonomous driving modes can be simulated, and a graphic user interface allows a test driver to select a target parking space on a display screen. …”
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Construction of Collision-Type Prediction Models Based on Pre-crash Data for Advanced Driver Assistance Systems by Wei Junhao, Yusuke Miyazaki, Koji Kitamura, Fusako Sato

“…Thus, they can be applied to autonomous driving systems (ADS) or advanced driver assistance systems (ADAS) to prevent serious accidents or minimize damage during collisions. …”
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Lightweight attention‐guided redundancy‐reuse network for real‐time semantic segmentation by Xuegang Hu, Shuhan Xu, Liyuan Jing

“…Abstract Semantic segmentation is a critical topic in computer vision, and it has numerous practical applications, including mobile devices, autonomous driving, and many other fields. However, in these application scenarios, it is often essential for the segmentation models to achieve a balance between efficiency and performance. …”
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ARTIFICIAL INTELLIGENCE (AI) BASED CONTRACTS PROCUREMENT: EXAMINING THE INFLUENCE OF BIG DATA, MACHINE LEARNING, INTERNET OF THINGS, EMPLOYEE SKILLS & RESOURCES AND LEADERSHIP ON P... by Omar Al-Sadhan, Muhammad Awais Bhatti

“…On the other hand, (machine learning and autonomous driving) had no significant impact on cost reduction. …”
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STABILITY CONTROL MODELLING UNDER DYNAMIC MOTION SCENARIO OF A DIFFERENTIAL DRIVE ROBOT by ADEDOTUN O. OWOJORI, KAYODE F. AKINGBADE, WALIU O. APENA, ERASTUS O. OGUNTI

“… Intelligence incorporated in many devices makes it easier to achieve self-balancing and autonomous driving in differential drive robot. Basically, differential drive robotic system describes an unstable, nonlinear system related to an inverted pendulum. …”
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Monocular 3D Object Detection Based on Pseudo Multimodal Information Extraction and Keypoint Estimation by Dan Zhao, Chaofeng Ji, Guizhong Liu

“…Three-dimensional object detection is an essential and fundamental task in the field of computer vision which can be widely used in various scenarios such as autonomous driving and visual navigation. In view of the current insufficient utilization of image information in current monocular camera-based 3D object detection algorithms, we propose a monocular 3D object detection algorithm based on pseudo-multimodal information extraction and keypoint estimation. …”
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Trustworthy Learning and Uncertainty Quantification under Constraints by Shen, Maohao

“…Machine learning techniques have become increasingly important in a wide range of fields, including medicine, finance, and autonomous driving. While state-of-theart machine learning models can achieve promising prediction performance, there is an increasing need for reliable and trustworthy machine learning techniques, which requires the models to impose other capabilities, such as privacy preservation, computational efficiency, interpretability, robustness, and uncertainty quantification. …”
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