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2020 Index IEEE Transactions on Intelligent Transportation Systems Vol. 21

2020 IEEE transactions on intelligent transportation systems (Print)  
., +, TITS Sept. 2020 3766-3776 Coarse-to-Fine Deep Learning of Continuous Pedestrian Orientation Based on Spatial Co-Occurrence Feature.  ...  Baqui, M., +, TITS Feb. 2020 580-589 Image recognition Automatic Traffic Sign Detection and Recognition Using SegU-Net and a Modified Tversky Loss Function With L1-Constraint.  ...  R Radar clutter Outliers-Robust CFAR Detector of Gaussian Clutter Based on the Truncated-Maximum-Likelihood-Estimator in SAR Imagery. Ai, J., 2039 -2049  ... 
doi:10.1109/tits.2020.3048827 fatcat:ab6he3jkfjboxg7wa6pagbggs4

Vision-Based Autonomous Vehicle Systems Based on Deep Learning: A Systematic Literature Review

Monirul Islam Pavel, Siok Yee Tan, Azizi Abdullah
2022 Applied Sciences  
It is expected to offer a pathway for the rapid development of cost-efficient and more secure practical autonomous vehicle systems.  ...  However, the AVS is still far away from mass production because of the high cost of sensor fusion and a lack of combination of top-tier solutions to tackle uncertainty on roads.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app12146831 fatcat:qkeylw67sngrtmmgwa2r3ue3ii

Towards holistic scene understanding: Semantic segmentation and beyond [article]

Panagiotis Meletis
2022 arXiv   pre-print
In Chapter 2 we design a framework of hierarchical classifiers over a single convolutional backbone, and train it end-to-end on a combination of pixel-labeled datasets, improving generalizability and the  ...  This dissertation addresses visual scene understanding and enhances segmentation performance and generalization, training efficiency of networks, and holistic understanding.  ...  Finalizing my PhD and looking back at my life as a researcher, I have only beautiful memories and experiences to think of.  ... 
arXiv:2201.07734v1 fatcat:qdqnjqn75rff7kyja2iwer75my

Recent Advances in Vision-Based On-Road Behaviors Understanding: A Critical Survey

Rim Trabelsi, Redouane Khemmar, Benoit Decoux, Jean-Yves Ertaud, Rémi Butteau
2022 Sensors  
We also finally provide a comprehensive discussion leading us to identify novel research directions some of which have been implemented and validated in our current smart mobility research work.  ...  a comprehensive understanding of approaches and techniques.  ...  to identify visual attributes for both tasks [21] .  ... 
doi:10.3390/s22072654 pmid:35408269 pmcid:PMC9003377 fatcat:2vrmgz3b25eyxbijeurx5aijv4

Scanning the Issue

Azim Eskandarian
2022 IEEE transactions on intelligent transportation systems (Print)  
This article investigates the influence of an external humanmachine interface (eHMI) for automated vehicles on pedestrian behavior in a parking lot.  ...  To promote the international standardization of novel signaling devices, this study is conducted in an international context in three countries.  ...  First, the authors construct a Bayesian network to analyze the delay parameters and select delay factors for visualization.  ... 
doi:10.1109/tits.2022.3160062 fatcat:4gklzaonfzcehnvps6oge35fwe

Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art [article]

Joel Janai, Fatma Güney, Aseem Behl, Andreas Geiger
2021 arXiv   pre-print
This book attempts to narrow this gap by providing a survey on the state-of-the-art datasets and techniques.  ...  , scene understanding, and end-to-end learning for autonomous driving.  ...  Traffic Sign Detection Reliable detection and recognition of traffic signs are essential for autonomous vehicles.  ... 
arXiv:1704.05519v3 fatcat:xiintiarqjbfldheeg2hsydyra

Drosophila-Inspired 3D Moving Object Detection Based on Point Clouds [article]

Li Wang, Dawei Zhao, Tao Wu, Hao Fu, Zhiyu Wang, Liang Xiao, Xin Xu, Bin Dai
2020 arXiv   pre-print
Designing neural circuits with different connection modes, the approach searches for motion areas in a coarse-to-fine fashion and extracts point clouds of each motion area to form moving object proposals  ...  An improved 3D object detection network is then used to estimate the point clouds of each proposal and efficiently generates the 3D bounding boxes and the object categories.  ...  As shown in Fig. 1 , the proposed approach combines the shallow visual neural pathway of Drosophila with a brain-inspired cognitive neural network to implement motion detection and object recognition,  ... 
arXiv:2005.02696v1 fatcat:27gvze4k4vex7plllgapjfhlgq

Applications of Deep Learning in Intelligent Transportation Systems

Arya Ketabchi Haghighat, Varsha Ravichandra-Mouli, Pranamesh Chakraborty, Yasaman Esfandiari, Saeed Arabi, Anuj Sharma
2020 Journal of Big Data Analytics in Transportation  
company's performance, and advanced driver-less vehicle development to a new stage.  ...  These improvements have facilitated traffic management and traffic planning, increased safety and security in transit roads, decreased costs of maintenance, optimized public transportation and ride-sharing  ...  The majority of the visual recognition work such as vehicle and pedestrian detection, traffic sign recognition, etc. have focused on autonomous driving or in-vehicle cameras.  ... 
doi:10.1007/s42421-020-00020-1 fatcat:fmlclttbknckjgno7vpisdyz3m

Learning Neural Textual Representations for Citation Recommendation

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
Triplet Networks Using Bayesian Updating Theorem DAY 1 -Jan 12, 2021 Leo, Marco; Carcagni, Pierluigi; Distante, Cosimo 1997 A Systematic Investigation on End-To-End Deep Recognition of Grocery  ...  396 A General Framework for Small Object Detection Leveraging on Simultaneous Unsupervised Super-resolution Initialization Using Perlin Noise for Training Networks with a Limited Amount of Data DAY 4  ... 
doi:10.1109/icpr48806.2021.9412725 fatcat:3vge2tpd2zf7jcv5btcixnaikm

Visual and Object Geo-localization: A Comprehensive Survey [article]

Daniel Wilson, Xiaohan Zhang, Waqas Sultani, Safwan Wshah
2021 arXiv   pre-print
, the fields of visual and object geo-localization have emerged due to its significant impact on a wide range of applications such as augmented reality, robotics, self-driving vehicles, road maintenance  ...  We will provide an in-depth study, including a summary of popular algorithms, a description of proposed datasets, and an analysis of performance results to illustrate the current state of each field.  ...  polygon surrounding the sign, and a list of images in which the traffic signs.  ... 
arXiv:2112.15202v1 fatcat:ipwas72ro5ho5fjiakm6de7ji4

Deep Learning in Mobile and Wireless Networking: A Survey [article]

Chaoyun Zhang, Paul Patras, Hamed Haddadi
2019 arXiv   pre-print
Upcoming 5G systems are evolving to support exploding mobile traffic volumes, agile management of network resource to maximize user experience, and extraction of fine-grained real-time analytics.  ...  In this paper we bridge the gap between deep learning and mobile and wireless networking research, by presenting a comprehensive survey of the crossovers between the two areas.  ...  The MLP is subsequently used to estimate the coarse position of targets. The authors further introduce an HMM to fine-tune the predictions based on temporal properties of data.  ... 
arXiv:1803.04311v3 fatcat:awuvyviarvbr5kd5ilqndpfsde

Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review

Mahdi Rezaei, Mahsa Shahidi
2020 Social Science Research Network  
We aim to convey a useful intuition through this paper towards the goal of handling complex learning tasks more similar to the way humans learn.  ...  automated detection = recognition systems using ZSL.  ...  [179] uses a unified probabilistic model based on the Bayesian Network (BN) [110] that discovers and captures both object-dependent and object-independent relationships to overcome the problem of  ... 
doi:10.2139/ssrn.3624379 fatcat:yifnxv46rjf6pgndowkxzmo5o4

Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review

Mahdi Rezaei, Mahsa Shahidi
2020 Intelligence-Based Medicine  
We aim to convey a useful intuition through this paper towards the goal of handling complex learning tasks more similar to the way humans learn.  ...  automated detection / recognition systems using ZSL.  ...  [179] uses a unified probabilistic model based on the Bayesian Network (BN) [110] that discovers and captures both object-dependent and object-independent relationships to overcome the problem of  ... 
doi:10.1016/j.ibmed.2020.100005 pmid:33043311 pmcid:PMC7531283 fatcat:qzyaf7gpufhermyg5gvank5cja

Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review [article]

Mahdi Rezaei, Mahsa Shahidi
2020 arXiv   pre-print
We aim to convey a useful intuition through this paper towards the goal of handling complex computer vision learning tasks more similar to the way humans learn.  ...  datasets, prepared by an expert human to train the network model.  ...  [61] uses a unified probabilistic model based on the Bayesian Network (BN) [62] that discovers and captures both object-dependent and objectindependent relationships to overcome the problem of relating  ... 
arXiv:2004.14143v2 fatcat:erh6xyog7bb5vofcebkk2zxumm

Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey [article]

Julian Wörmann, Daniel Bogdoll, Etienne Bührle, Han Chen, Evaristus Fuh Chuo, Kostadin Cvejoski, Ludger van Elst, Tobias Gleißner, Philip Gottschall, Stefan Griesche, Christian Hellert, Christian Hesels (+34 others)
2022 arXiv   pre-print
As a consequence, the reliable use of these models, especially in safety-critical applications, is a huge challenge.  ...  The reasons for this are manifold and range from time and cost constraints to ethical considerations.  ...  In [626] , it is used to learn the parameters of an objective function that is subsequently used for behavior (coarse-scale) and trajectory (fine-scale) planning.  ... 
arXiv:2205.04712v1 fatcat:u2bgxr2ctnfdjcdbruzrtjwot4
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