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Deep Learning for Omnidirectional Vision: A Survey and New Perspectives [article]

Hao Ai, Zidong Cao, Jinjing Zhu, Haotian Bai, Yucheng Chen, Lin Wang
2022 arXiv   pre-print
In recent years, the availability of customer-level 360 cameras has made omnidirectional vision more popular, and the advance of deep learning (DL) has significantly sparked its research and applications  ...  ; (iii) A summarization of the latest novel learning strategies and applications; (iv) An insightful discussion of the challenges and open problems by highlighting the potential research directions to  ...  The satellite stage predicts depth maps and segmentation maps from satellite images. The geo-transformation stage transforms the output of the satellite stage into the panoramas.  ... 
arXiv:2205.10468v2 fatcat:73fks33oafa6zgxliccydvdbeq

GeoAI for Large-Scale Image Analysis and Machine Vision: Recent Progress of Artificial Intelligence in Geography

Wenwen Li, Chia-Yu Hsu
2022 ISPRS International Journal of Geo-Information  
While different applications tend to use diverse types of data and models, we summarized six major strengths of GeoAI research, including (1) enablement of large-scale analytics; (2) automation; (3) high  ...  in a variety of image analysis and machine vision tasks.  ...  For the radar echo map-based method, each map is transformed into an image and fed into the prediction algorithm/model.  ... 
doi:10.3390/ijgi11070385 fatcat:yyzi46anyfcjrjuzcjfhbczo5y

Estimating Building Energy Efficiency From Street View Imagery, Aerial Imagery, and Land Surface Temperature Data [article]

Kevin Mayer, Lukas Haas
2022 arXiv   pre-print
Lastly, we extend our analysis by studying the predictive power of each data source in an ablation study.  ...  We find that the best end-to-end deep learning model achieves a macro-averaged F1-score of 62.06% and outperforms the k-NN and SVM-based baseline models by 5.62 to 11.47 percentage points, respectively  ...  This indicates that the signals identified in the different data sources are complementary and can be used in combination to better predict the energy efficiency of buildings.  ... 
arXiv:2206.02270v2 fatcat:iqwowwdlfzbrlob2nftsfbpkri

Internet of Things and Machine Learning Applications for Smart Precision Agriculture [chapter]

R. Sivakumar, B. Prabadevi, G. Velvizhi, S. Muthuraja, S. Kathiravan, M. Biswajita, A. Madhumathi
2021 Ubiquitous Computing [Working Title]  
This advancement could empower agricultural management systems to handle farm data in an orchestrated manner and increase the agribusiness by formulating effective strategies.  ...  Agriculture needs to be assisted by modern automation to produce the maximum yield. The recent development in technology has a significant impact on agriculture.  ...  Radio signals broadcasted from the G.P.S. satellites monitored by receivers [3] . A GPS position is usually determined by simultaneously measuring the distance to at least three satellites.  ... 
doi:10.5772/intechopen.97679 fatcat:2stbj72a3bf67bgs72swxtglf4

6G Internet of Things: A Comprehensive Survey

Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, Dusit Niyato, Octavia Dobre, H. Vincent Poor
2021 IEEE Internet of Things Journal  
In this article, we explore the emerging opportunities brought by 6G technologies in IoT networks and applications, by conducting a holistic survey on the convergence of 6G and IoT.  ...  We first shed light on some of the most fundamental 6G technologies that are expected to empower future IoT networks, including edge intelligence, reconfigurable intelligent surfaces, space-air-ground-underwater  ...  However, unlike [62] , this scheme leverages THz base station density and the strength of THz signals for UAVs' location and trajectory estimation.  ... 
doi:10.1109/jiot.2021.3103320 fatcat:fgm4ndqp6napjlt3z4ikthdsfy

Machine Learning Based Indoor Localization Using Wi-Fi RSSI Fingerprints: An Overview

Navneet Singh, Sangho Choe, Rajiv Punmiya
2021 IEEE Access  
INDEX TERMS Machine learning, fingerprints, indoor localization, positioning, deep learning, received signal strength indicator, Wi-Fi.  ...  In recent years, many researchers have proposed a wide range of machine learning (ML)-based indoor localization approaches using Wi-Fi received signal strength indicator (RSSI) fingerprints.  ...  The authors of [113] proposed a Fourier transformation and minimization method that reduces the sparsity in radio maps by using a sparse group LASSO.  ... 
doi:10.1109/access.2021.3111083 fatcat:7o6zb7kycrgftfpsukuwnsl24m

6G Enabled Smart Infrastructure for Sustainable Society: Opportunities, Challenges, and Research Roadmap

Agbotiname Lucky Imoize, Oluwadara Adedeji, Nistha Tandiya, Sachin Shetty
2021 Sensors  
The 5G wireless communication network is currently faced with the challenge of limited data speed exacerbated by the proliferation of billions of data-intensive applications.  ...  Additionally, we present new use cases of the 6G technology in agriculture, education, media and entertainment, logistics and transportation, and tourism.  ...  • Handover management and good signal strength [272] . • Lack of ubiquitous connectivity. • Limited data rate with increasing distance.  ... 
doi:10.3390/s21051709 pmid:33801302 pmcid:PMC7958349 fatcat:2alvcdqlvfcq5chfkv4n3wftpu

Graph Neural Networks in IoT: A Survey [article]

Guimin Dong, Mingyue Tang, Zhiyuan Wang, Jiechao Gao, Sikun Guo, Lihua Cai, Robert Gutierrez, Bradford Campbell, Laura E. Barnes, Mehdi Boukhechba
2022 arXiv   pre-print
Deep learning models (e.g., convolution neural networks and recurrent neural networks) have been extensively employed in solving IoT tasks by learning patterns from multi-modal sensory data.  ...  In this survey, we present a comprehensive review of recent advances in the application of GNNs to the IoT field, including a deep dive analysis of GNN design in various IoT sensing environments, an overarching  ...  [268] proposed a semi-supervised soil moisture prediction framework by using self-attention based temporal GNN, using both remote satellite and weather data to predict the soil moisture by locations  ... 
arXiv:2203.15935v2 fatcat:jkqg5ukg5fezbewu5mr5hqsp4e

2020 Index IEEE Transactions on Vehicular Technology Vol. 69

2020 IEEE Transactions on Vehicular Technology  
Wu, R., +, TVT June 2020 6473-6484 Data-Driven Interference Localization Using a Single Satellite Based on Received Signal Strength.  ...  Forster, D., +, TVT March 2020 2398-2410 Data-Driven Interference Localization Using a Single Satellite Based on Received Signal Strength.  ...  Mixture models Human Mobility Prediction Using Sparse Trajectory Data.  ... 
doi:10.1109/tvt.2021.3055470 fatcat:536l4pgnufhixneoa3a3dibdma

The Road Towards 6G: A Comprehensive Survey [article]

Wei Jiang, Bin Han, Mohammad Asif Habibi, Hans Dieter Schotten
2021 arXiv   pre-print
by shedding light on its key driving factors, in which we predict the explosive growth of mobile traffic until 2030, and envision potential use cases and usage scenarios.  ...  At this crossroad, an overview of the current state of the art and a vision of future communications are definitely of interest.  ...  , and much shorter propagation distance that corresponds to higher signal strength and lower latency [143] .  ... 
arXiv:2102.01420v1 fatcat:7pexxlo3pjfwlls6dl4lvh77iq

2021 Index IEEE Transactions on Industrial Informatics Vol. 17

2021 IEEE Transactions on Industrial Informatics  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  Gao, J., +, TII Feb. 2021 971-979 Signal Estimation in Cognitive Satellite Networks for Satellite-Based Industrial Internet of Things.  ...  ., +, TII June 2021 3857-3868 Improved Short-Term Speed Prediction Using Spatiotemporal-Vision-Based Deep Neural Network for Intelligent Fuel Cell Vehicles.  ... 
doi:10.1109/tii.2021.3138206 fatcat:ulsazxgmpfdmlivigjqgyl7zre

IEEE Access Special Section Editorial: AI-Driven Big Data Processing: Theory, Methodology, and Applications

Zhanyu Ma, Sunwoo Kim, Pascual Martinez-Gomez, Jalil Taghia, Yi-Zhe Song, Huiji Gao
2020 IEEE Access  
In the article, ''Big data processing architecture for radio signals empowered by deep learning: Concept, experiment, applications, and challenges,'' by Zheng et al., a big data processing architecture  ...  An accurate saliency map will be useful for subsequent tasks. However, in most saliency maps predicted by existing models, objects regions are very blurred and the edges of objects are irregular.  ...  First, the authors improve the Self-Organizing Feature Map (SOFM) algorithm and use the optimized SOFM clustering algorithm to cluster the data set.  ... 
doi:10.1109/access.2020.3035461 fatcat:rt7ejtponrfexigie4cfpt7gd4

Transport-domain applications of widely used data sources in the smart transportation: A survey [article]

Sina Dabiri, Kevin Heaslip
2018 arXiv   pre-print
Secondly, as the most salient feature of this study, the transport-domain applications of each data source that have been conducted by the previous studies are reviewed and classified into the main groups  ...  At each location on earth, at least four satellites are visible. A GPS device receives the radio signals broadcasted by the satellites.  ...  Global Positioning System Operational mechanism of Global Positioning System GPS, also called NAVSTAR by the US Department of Defense, is a satellite-based navigation system built up by 24 satellites  ... 
arXiv:1803.10902v3 fatcat:tc67qy4x4vbtjb76qi6mbwrqy4

6G Ecosystem: Current Status and Future Perspective

Jagadeesha R Bhat, Salman A. AlQahtani
2021 IEEE Access  
Initially, we describe the instances that lead us to the vision of 6G. Later, we narrate some of the use cases and the KPIs essential to meet their performance requirement.  ...  This interdependency between multiple use cases is shown as uLLRS (low latency, reliability, and security) by an arrow in Fig 1(b) .  ...  In deep learning, fingerprint method uses CSI and received signal strength as learning data.  ... 
doi:10.1109/access.2021.3054833 fatcat:d5pkupvwobh45dp2k3jr67yrgu

A Survey on Machine-Learning Techniques for UAV-Based Communications

Petros S Bithas, Emmanouel T Michailidis, Nikolaos Nomikos, Demosthenes Vouyioukas, Athanasios G Kanatas
2019 Sensors  
In this context, the machine-learning (ML) framework is expected to provide solutions for the various problems that have already been identified when UAVs are used for communication purposes.  ...  In this article, we provide a detailed survey of all relevant research works, in which ML techniques have been used on UAV-based communications for improving various design and functional aspects such  ...  based on the received signal strengths.  ... 
doi:10.3390/s19235170 pmid:31779133 pmcid:PMC6929112 fatcat:pnur7lmpj5bj7poebmdfpd6bhi
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