Filters








31 Hits in 12.9 sec

Editorial: deep learning for 5G IoT systems

Xiaochun Cheng, Chengqi Zhang, Yi Qian, Moayad Aloqaily, Yang Xiao
2021 International Journal of Machine Learning and Cybernetics  
The paper "Improved VGG model based efficient traffic sign recognition for safe driving in 5G scenarios" proposed an improved VGG convolutional neural network.  ...  The paper "Deep Transfer Learning-based Network Traffic Classification for Scarce Dataset in 5G IoT Systems" presents a traffic classification method based on deep transfer learning for 5G IoT scenarios  ... 
doi:10.1007/s13042-021-01382-w pmid:34306244 pmcid:PMC8287284 fatcat:ialozvaokvcljp4mxd2j6dp6ty

Computing Systems for Autonomous Driving: State-of-the-Art and Challenges [article]

Liangkai Liu, Sidi Lu, Ren Zhong, Baofu Wu, Yongtao Yao, Qingyang Zhang, Weisong Shi
2020 arXiv   pre-print
The real traffic environment is too complicated for current autonomous driving computing systems to understand and handle.  ...  ., DSRC, C-V2X, 5G) have pushed the horizon of autonomous driving, which automates the decision and control of vehicles by leveraging the perception results based on multiple sensors.  ...  Seo [231] proposed a machine learning-based method to improve the recognition of work zone signs.  ... 
arXiv:2009.14349v3 fatcat:xmo6mxucizf33hu2n2ddoy4xsy

Deep Learning Serves Traffic Safety Analysis: A Forward-looking Review [article]

Abolfazl Razi, Xiwen Chen, Huayu Li, Hao Wang, Brendan Russo, Yan Chen, Hongbin Yu
2022 arXiv   pre-print
This paper explores Deep Learning (DL) methods that are used or have the potential to be used for traffic video analysis, emphasizing driving safety for both Autonomous Vehicles (AVs) and human-operated  ...  We also review existing open-source tools and public datasets that can help train DL models. To be more specific, we review exemplary traffic problems and mentioned requires steps for each problem.  ...  Junsuo Qu and Greg Leeming for his insightful comments.  ... 
arXiv:2203.10939v2 fatcat:oml733wvjfh3blne4h7kg5y3du

Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things [article]

Jing Zhang, Dacheng Tao
2020 arXiv   pre-print
Then, we present progress in AI research for IoT from four perspectives: perceiving, learning, reasoning, and behaving.  ...  Artificial intelligence (AI), especially deep learning, is now a proven success in various areas including computer vision, speech recognition, and natural language processing.  ...  ) human-machine interaction systems (e.g., control television) based on hand gesture recognition [122] , [124] in smart homes, share the similar techniques for traffic sign language recognition in smart  ... 
arXiv:2011.08612v1 fatcat:dflut2wdrjb4xojll34c7daol4

Recent Trends in AI-Based Intelligent Sensing

Abhishek Sharma, Vaidehi Sharma, Mohita Jaiswal, Hwang-Cheng Wang, Dushantha Nalin K. Jayakody, Chathuranga M. Wijerathna Basnayaka, Ammar Muthanna
2022 Electronics  
This survey provides a comprehensive summary of recent research on AI-based algorithms for intelligent sensing.  ...  The methods based on AI enable a computer to learn and monitor activities by sensing the source of information in a real-time environment.  ...  In order to work on realistic images taken from a smartphone, a transfer learning-based pre-trained model on ImageNet of VGG-16 is used for training deep neural networks and for verifying the approach.  ... 
doi:10.3390/electronics11101661 fatcat:smuark52zjfjverlwlf2tzjpfa

Program

2020 2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)  
network transmission services according to different usage scenarios. 5G and SDN are considered the basis for high-quality mobile VR streaming applications.  ...  In this paper, a deep learning-based violin action recognition is proposed.  ...  For group convolution, the VGG-like plain network is used to construct the model.  ... 
doi:10.1109/icce-taiwan49838.2020.9258230 fatcat:g25vw7mzvradxna2grlzp6kgiq

Deep Learning for IoT Big Data and Streaming Analytics: A Survey [article]

Mehdi Mohammadi, Ala Al-Fuqaha, Sameh Sorour, Mohsen Guizani
2018 arXiv   pre-print
improving technology.  ...  Based on the nature of the application, these devices will result in big or fast/real-time data streams.  ...  [125] presented a traffic sign recognition system based on DNNs of convolutional and max-pooling layers.  ... 
arXiv:1712.04301v2 fatcat:kr64lst37rhlfcpaxckgzlozvu

Survey of Cooperative Advanced Driver Assistance Systems: From a Holistic and Systemic Vision

Juan Felipe González-Saavedra, Miguel Figueroa, Sandra Céspedes, Samuel Montejo-Sánchez
2022 Sensors  
We address the remote operation of this C-ADAS based on the Internet of vehicles (IoV) paradigm, as well as the involved enabling technologies.  ...  We describe the state of the art and the research challenges present in the development of C-ADAS.  ...  Specifically, they focus on artificial vision, radar, and LIDAR technologies of exteroceptive sensors applied in tasks as (i) automatic traffic-sign detection and recognition, (ii) perception of the environment  ... 
doi:10.3390/s22083040 pmid:35459025 pmcid:PMC9024749 fatcat:cro4c577vjgldpznxec7cnbxni

Explainable AI for B5G/6G: Technical Aspects, Use Cases, and Research Challenges [article]

Shen Wang, M.Atif Qureshi, Luis Miralles-Pechuaán, Thien Huynh-The, Thippa Reddy Gadekallu, Madhusanka Liyanage
2021 arXiv   pre-print
These decisions can range widely, from network resource allocation to collision avoidance for self-driving cars.  ...  Moreover, we summarised the lessons learned from the recent attempts and outlined important research challenges in applying XAI for building 6G systems.  ...  safe and efficient operation on execute driving activities.  ... 
arXiv:2112.04698v1 fatcat:y7ss4opmrjbsbjm3ip2vgkkgky

Deep Learning Sensor Fusion for Autonomous Vehicle Perception and Localization: A Review

Jamil Fayyad, Mohammad A. Jaradat, Dominique Gruyer, Homayoun Najjaran
2020 Sensors  
technologies, such as 5G.  ...  management, traffic optimization, comfort).  ...  , road signs, traffic signals, and road curbs.  ... 
doi:10.3390/s20154220 pmid:32751275 pmcid:PMC7436174 fatcat:fuhotalv2fdmbmpgx6llkp4xse

Machine Learning for Security in Vehicular Networks: A Comprehensive Survey [article]

Anum Talpur, Mohan Gurusamy
2021 arXiv   pre-print
In this paper, we present a comprehensive survey of ML-based techniques for different security issues in vehicular networks.  ...  The limitations and challenges in using ML-based methods in vehicular networks are discussed. Finally, we present observations and lessons learned before we conclude our work.  ...  The performance evaluation of the attack model is done using three different complex traffic scenarios.  ... 
arXiv:2105.15035v2 fatcat:5z6aqlvosjgf3o3amts3k6toxu

Program

2021 2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)  
However, for the classification of fine-grained actions, current action recognition models still need improvement.  ...  safely.  ... 
doi:10.1109/icce-tw52618.2021.9602919 fatcat:aetmvxb7hfah7iuucbamos2wgu

Edge Intelligence: Architectures, Challenges, and Applications [article]

Dianlei Xu, Tong Li, Yong Li, Xiang Su, Sasu Tarkoma, Tao Jiang, Jon Crowcroft, Pan Hui
2020 arXiv   pre-print
Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis in locations close to where data is captured based on artificial intelligence.  ...  In this paper, we present a thorough and comprehensive survey on the literature surrounding edge intelligence.  ...  driving scenarios.  ... 
arXiv:2003.12172v2 fatcat:xbrylsvb7bey5idirunacux6pe

A Methodological Review on Prediction of Multi-stage Hypovigilance Detection Systems using Multimodal Features

Qaisar Abbas, Abdullah Alsheddy
2021 IEEE Access  
this project entitled "Analysis and Modeling of Cloud Computing for Drivers Fatigue and Vigilance Monitoring" under the grant no. (0001-008-11-17-3).  ...  ACKNOWLEDGMENT The authors would like to thank King Abdulaziz City for Science and Technology (KACST) and Deanship of Scientific Research center at Al Imam Mohammad ibn Saud Islamic university, for financing  ...  The MFRNN model was used to improve the efficiency of the drowsiness detection system.  ... 
doi:10.1109/access.2021.3068343 fatcat:rbqdxyabsvah3ginlkd3gqkrwu

Program

2022 2022 International Conference on Decision Aid Sciences and Applications (DASA)  
The results conclude that the proposed method can detect AD patients efficiently. The proposed method can further be used to detect other neurological disorders.  ...  This paper aims to propose a model for safe zone selection during air pollution disasters.  ...  Three different Deep CNN models for our study: VGG -16, Inception-V3, and Xception to classify Alzheimer's disease.  ... 
doi:10.1109/dasa54658.2022.9765271 fatcat:ttqppf4j3navnaxe653mrzmezi
« Previous Showing results 1 — 15 out of 31 results