Artificial Intelligence and Smart Vehicles [[electronic resource] ] : First International Conference, ICAISV 2023, Tehran, Iran, May 24-25, 2023, Revised Selected Papers / / edited by Mehdi Ghatee, S. Mehdi Hashemi |
Edizione | [1st ed. 2023.] |
Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
Descrizione fisica | 1 online resource (230 pages) |
Disciplina | 670.28563 |
Collana | Communications in Computer and Information Science |
Soggetto topico |
Artificial intelligence
Image processing - Digital techniques Computer vision Signal processing Computer networks Machine learning Artificial Intelligence Computer Imaging, Vision, Pattern Recognition and Graphics Signal, Speech and Image Processing Computer Communication Networks Machine Learning |
ISBN | 3-031-43763-2 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Local and Global Contextual Features Fusion for Pedestrian Intention Prediction -- Routes analysis and dependency detection based on traffic volume: a deep learning approach -- Road Sign Classification using Transfer Learning and Pre-Trained CNN Models -- Improving Safe Driving with Diabetic Retinopathy Detection -- A Bibliometric Analysis on Artificial Intelligence and Smart Vehicles -- Convolutional Neural Network and Long Short Term Memory on Inertial Measurement Unit sensors for Gait Phase Detection -- Real-time mobile mixed-character license plate recognition via deep learning convolutional neural network -- Evaluation of Drivers’ Hazard Perception in Simultaneous Longitudinal and Lateral Control of Vehicle Using a Driving Simulator -- Driver Identification by An Ensemble of CNNs Obtained from Majority-Voting Model Selection -- State-of-the-Art Analysis of the Performance of the Sensors Utilized in Autonomous Vehicles in Extreme Conditions -- Semantic Segmentation using Events and Combination of Events and Frames -- Deep learning-based concrete crack detection using YOLO architecture -- Generating Control Command for an Autonomous Vehicle Based on Environmental Information -- Fractal-Based Spatiotemporal Predictive Model for Car Crash Risk Assessment. |
Record Nr. | UNISA-996558570503316 |
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Artificial Intelligence and Smart Vehicles : First International Conference, ICAISV 2023, Tehran, Iran, May 24-25, 2023, Revised Selected Papers / / edited by Mehdi Ghatee, S. Mehdi Hashemi |
Edizione | [1st ed. 2023.] |
Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
Descrizione fisica | 1 online resource (230 pages) |
Disciplina |
670.28563
629.046 |
Collana | Communications in Computer and Information Science |
Soggetto topico |
Artificial intelligence
Image processing - Digital techniques Computer vision Signal processing Computer networks Machine learning Artificial Intelligence Computer Imaging, Vision, Pattern Recognition and Graphics Signal, Speech and Image Processing Computer Communication Networks Machine Learning |
ISBN | 3-031-43763-2 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Local and Global Contextual Features Fusion for Pedestrian Intention Prediction -- Routes analysis and dependency detection based on traffic volume: a deep learning approach -- Road Sign Classification using Transfer Learning and Pre-Trained CNN Models -- Improving Safe Driving with Diabetic Retinopathy Detection -- A Bibliometric Analysis on Artificial Intelligence and Smart Vehicles -- Convolutional Neural Network and Long Short Term Memory on Inertial Measurement Unit sensors for Gait Phase Detection -- Real-time mobile mixed-character license plate recognition via deep learning convolutional neural network -- Evaluation of Drivers’ Hazard Perception in Simultaneous Longitudinal and Lateral Control of Vehicle Using a Driving Simulator -- Driver Identification by An Ensemble of CNNs Obtained from Majority-Voting Model Selection -- State-of-the-Art Analysis of the Performance of the Sensors Utilized in Autonomous Vehicles in Extreme Conditions -- Semantic Segmentation using Events and Combination of Events and Frames -- Deep learning-based concrete crack detection using YOLO architecture -- Generating Control Command for an Autonomous Vehicle Based on Environmental Information -- Fractal-Based Spatiotemporal Predictive Model for Car Crash Risk Assessment. |
Record Nr. | UNINA-9910746969003321 |
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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