Improved Search Algorithm of Digital Speckle Pattern Based on PSO and IC-GN by Qiang Chen, Zhixin Tie, Liang Hong, Youtian Qu, Dengwen Wang

“…In the future, it will even be inextricably linked to the Internet of Things, autonomous driving, deep learning and other fields. For a given hardware condition, it is of great significance to improve the efficiency of integer-pixel search and increase the accuracy and efficiency of the sub-pixel algorithm. …”
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Deep Learning for Visual SLAM: The State-of-the-Art and Future Trends by Margarita N. Favorskaya

“…Although the implementation of VSLAM methods is far from perfect and complete, recent research in deep learning has yielded promising results for applications such as autonomous driving and navigation, service robots, virtual and augmented reality, and pose estimation. …”
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Intelligent Data-Enabled Task Offloading for Vehicular Fog Computing by Ahmed S. Alfakeeh, Muhammad Awais Javed

“…Fog computing is a key component of future intelligent transportation systems (ITSs) that can support the high computation and large storage requirements needed for autonomous driving applications. A major challenge in such fog-enabled ITS networks is the design of algorithms that can reduce the computation times of different tasks by efficiently utilizing available computational resources. …”
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Semantic segmentation of urban environments: Leveraging U-Net deep learning model for cityscape image analysis. by T S Arulananth, P G Kuppusamy, Ramesh Kumar Ayyasamy, Saadat M Alhashmi, M Mahalakshmi, K Vasanth, P Chinnasamy

“…These include urban planning, transportation management, autonomous driving, and smart city efforts. Through rich context and insights, semantic segmentation helps decision-makers and stakeholders make educated decisions for sustainable and effective urban development. …”
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A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles by Jae Kyu Suhr, Ho Gi Jung

“…An automatic parking system is an essential part of autonomous driving, and it starts by recognizing vacant parking spaces. …”
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The Distributed HTAP Architecture for Real-Time Analysis and Updating of Point Cloud Data by Juhyun Kim, Changjoo Moon

“…Updating the most recent set of point cloud data is critical in autonomous driving environments. However, existing systems for point cloud data management often fail to ensure real-time updates or encounter situations in which data cannot be effectively refreshed. …”
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INVESTIGATION OF THE RADIOMETRIC BEHAVIOUR OF A LOW-COST AUTOMOTIVE LIDAR SENSOR by Z. Zhang, Z. Zeng, J. Boehm

“…A new category of low-cost LiDAR sensors for autonomous driving has become available with similar specifications. …”
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Attention-Gate-Based Model with Inception-like Block for Single-Image Dehazing by Cheng-Ying Tsai, Chieh-Li Chen

“…It also reduces visibility and degrades the performance of computer vision algorithms in autonomous driving applications, which may jeopardize car driving safety. …”
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Targeting Lane-Level Map Matching for Smart Vehicles: Construction of High-Definition Road Maps Based on GIS by Tian Lei, Gaoyao Xiao, Xiaohong Yin

“…However, traditional road maps for vehicle navigation systems are not sufficient to meet the requirements of intelligent vehicle systems (e.g., autonomous driving). The present work comes up with a method of generating high-definition map models based on the geographic information system (GIS). …”
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Real-Time Embedded Implementation of Improved Object Detector for Resource-Constrained Devices by Niranjan Ravi, Mohamed El-Sharkawy

“…Self-navigating delivery robots are recent trends in A.I. applications such as multitarget object detection, image classification, and segmentation to tackle sociotechnical challenges, including the development of autonomous driving vehicles, surveillance systems, intelligent transportation, and smart traffic monitoring systems. …”
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Ego‐lane index‐aware vehicular localisation using the DeepRoad Network for urban environments by Soomok Lee, Jinwoo Choi, Seung‐Woo Seo

“…Abstract Accurate real‐time localisation is crucial for various autonomous driving applications. Numerous methods for localization, combining various kinds of input such as data from environmental sensors, inertial measurement units, and the Global Positioning System, have been proposed. …”
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A Visual Navigation System for UAV under Diverse Illumination Conditions by Jiang Hai, Yutong Hao, Fengzhu Zou, Fang Lin, Songchen Han

“…Moreover, we also prove that our method is also effective in other practical tasks (e.g. autonomous driving).…”
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Balancing Privacy and Accuracy: Exploring the Impact of Data Anonymization on Deep Learning Models in Computer Vision by Jun Ha Lee, Su Jeong You

“…Computer vision has become indispensable in various applications, including autonomous driving, medical imaging, security and surveillance, robotics, and pattern recognition. …”
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Deep Active Learning for Computer Vision Tasks: Methodologies, Applications, and Challenges by Mingfei Wu, Chen Li, Zehuan Yao

“…Deep active learning plays a crucial role in computer vision tasks, especially in label-insensitive scenarios, such as hard-to-label tasks (medical images analysis) and time-consuming tasks (autonomous driving). However, deep active learning still has some challenges, such as unstable performance and dirty data, which are future research trends. …”
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LiMOX—A Point Cloud Lidar Model Toolbox Based on NVIDIA OptiX Ray Tracing Engine by Relindis Rott, David J. Ritter, Stefan Ladstätter, Oliver Nikolić, Marcus E. Hennecke

“…Virtual testing and validation are building blocks in the development of autonomous systems, in particular autonomous driving. Perception sensor models gained more attention to cover the entire tool chain of the sense–plan–act cycle, in a realistic test setup. …”
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Anytime Tree-Based Trajectory Planning for Urban Driving by Christoph Ziegler, Jurgen Adamy

“…The personal mobility of the future will be changed significantly by autonomous driving. To realize this vision, the complex task of trajectory planning needs to be solved. …”
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GPS/DR Error Estimation for Autonomous Vehicle Localization by Byung-Hyun Lee, Jong-Hwa Song, Jun-Hyuck Im, Sung-Hyuck Im, Moon-Beom Heo, Gyu-In Jee

“…The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. …”
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Implementation and analysis of a parallel kalman filter algorithm for lidar localization based on CUDA technology by Lesia Mochurad

“…All of these factors can significantly affect the localization accuracy of autonomous driving systems. This emphasizes the need for other localization technologies, such as Lidar.Methods: The use of the Kalman filter in combination with Lidar can be very effective in various applications due to the synergy of their capabilities. …”
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A Hierarchical Forecasting Model of Pedestrian Crossing Behavior for Autonomous Vehicle by Guolin Yang, Erwin Jose Lopez Pulgarin, Guido Herrmann

“…Simulation of pedestrians in shared spaces poses a significant challenge in autonomous driving virtual testing. The simulation pedestrian model can respond to autonomous vehicle behaviour changes. …”
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A Review of the Bayesian Occupancy Filter by Marcelo Saval-Calvo, Luis Medina-Valdés, José María Castillo-Secilla, Sergio Cuenca-Asensi, Antonio Martínez-Álvarez, Jorge Villagrá

“…One of the most critical aspects addressed in both autonomous driving and robotics is environment perception, since it consists of the ability to understand the surroundings of the vehicle to estimate risks and make decisions on future movements. …”
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