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Integration of Vehicular Clouds and Autonomous Driving: Survey and Future Perspectives [article]

Yassine Maalej, Elyes Balti
2022 arXiv   pre-print
For decades, researchers on Vehicular Ad-hoc Networks (VANETs) and autonomous vehicles presented various solutions for vehicular safety and autonomy, respectively.  ...  Potentials for bridging the gap between these two worlds and creating synergies of these two technologies have recently started to attract significant attention of many companies and government agencies  ...  , HD mapping, energy efficiency, automated highway driving, accelerated deep learning, sensor fusion, HD mapping, etc.  ... 
arXiv:2201.02893v2 fatcat:bqnscosmqrfdvihexa4mhqv2dy

A Systematic Review on Affective Computing: Emotion Models, Databases, and Recent Advances [article]

Yan Wang, Wei Song, Wei Tao, Antonio Liotta, Dawei Yang, Xinlei Li, Shuyong Gao, Yixuan Sun, Weifeng Ge, Wei Zhang, Wenqiang Zhang
2022 arXiv   pre-print
strategies for multimodal affective analysis, and unsupervised learning models.  ...  Firstly, we introduce two typical emotion models followed by commonly used databases for affective computing.  ...  Compared with feature-level fusion, decision-level fusion [362] is performed easier, but ignores the relevance among features of different modalities.  ... 
arXiv:2203.06935v3 fatcat:h4t3omkzjvcejn2kpvxns7n2qe

Noisy Ocular Recognition Based on Three Convolutional Neural Networks

2017 Sensors  
In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security.  ...  Hence, many studies have proposed methods of using iris images captured by a visible light camera without the need for an additional illuminator.  ...  Training of CNN Model In order to verify the method suggested by this study for two-fold cross-validation, training of the CNN model was conducted by using the training data obtained through the data augmentation  ... 
doi:10.3390/s17122933 pmid:29258217 pmcid:PMC5751551 fatcat:2ldr2vbtunaq5hhpn5f5xoisia

Object exploration using vision and active touch

Chuanyu Yang, Nathan F. Lepora
2017 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)  
When vision is dominant, increasing the influence of touch over uni-modal vision (10 −2 ≤ σ ≤ 0.3), causes the perceptual errors to initially change very little, but then improve precipitously to the optimal  ...  Edge following with uni-modal vision or touch First, we verify that the tactile perception method (Sec. III-B) and the visual perception method (Sec.  ... 
doi:10.1109/iros.2017.8206542 dblp:conf/iros/YangL17 fatcat:l6plx3oppvef3ka67p7nhc6ucm

Biometric identification systems

Rodrigo de Luis-Garcı́a, Carlos Alberola-López, Otman Aghzout, Juan Ruiz-Alzola
2003 Signal Processing  
Fusion at di erent conceptual levels is described. Finally, a section on commercial issues provides the reader a perspective of the main companies currently involved in this ÿeld. ?  ...  Acknowledgements The authors acknowledge the Spanish CICYT for research Grant TIC2001-3808-C02.  ...  This framework basically changes scales and eliminates biases in the opinion quantities. Then a nonlinear function maps the opinions within the segment [0; 1].  ... 
doi:10.1016/j.sigpro.2003.08.001 fatcat:tkz6nqg57ffb5bipn5yb6r6sjy

TWO!EARS Deliverable D4.1 - Feedback-loop selection and listing (WP4: Active listening, feedback loops & integration of cross-modal information; FP7-ICT-2013-C TWO!EARS FET-Open Project 618075)

Jens Blauert, Thomas Walther
2019 Zenodo  
Also, multi-modal approaches have been reviewed and evaluated with regard to their value for Two!Ears. Her [...]  ...  This deliverable mainly entails our advance on the key task for the current project period, namely, task 4.1.  ...  • Task 4.3 -Cross-modal input For operations on cross-modal input, the Two!Ears system has been augmented with the MORSE robot simulator.  ... 
doi:10.5281/zenodo.2595244 fatcat:3oocvxholvgr3ecgubmq3uwxqa

6G Cognitive Information Theory: A Mailbox Perspective

Yixue Hao, Yiming Miao, Min Chen, Hamid Gharavi, Victor C. M. Leung
2021 Big Data and Cognitive Computing  
In order to solve the above challenges, we propose a 6G mailbox theory, namely a cognitive information carrier to enable distributed algorithm embedding for intelligence networking.  ...  Remote Sensing and Mapping Remote sensing refers to non-contact, remote-detection technology [87] .  ...  area network, and multi-modal patient-data fusion, diagnosis, and treatment.  ... 
doi:10.3390/bdcc5040056 fatcat:ffof5likzbhfnopa3yfaobznfa

Machine Learning and Deep Learning Approaches for Brain Disease Diagnosis: Principles and Recent Advances

Protima Khan, Md. Fazlul Kader, S. M. Riazul Islam, Aisha B. Rahman, Md. Shahriar Kamal, Masbah Uddin Toha, Kyung-Sup Kwak
2021 IEEE Access  
Through this study, we aim at finding the most accurate technique for detecting different brain diseases which can be employed for future betterment.  ...  Thus, because of the variability of brain diseases, existing diagnosis or detection systems are becoming challenging and are still an open problem for research.  ...  Here, they have used a multi-modal feature extractor and 10-fold cross validation for testing purposes.  ... 
doi:10.1109/access.2021.3062484 fatcat:lmhp34ad3zdexb5y4bt5ksntia

Medical Image Analysis on Left Atrial LGE MRI for Atrial Fibrillation Studies: A Review [article]

Lei Li and Veronika A. Zimmer and Julia A. Schnabel and Xiahai Zhuang
2022 arXiv   pre-print
This paper aims to provide a systematic review on computing methods for LA cavity, wall, scar and ablation gap segmentation and quantification from LGE MRI, and the related literature for AF studies.  ...  Although several methods have been proposed, especially for LA segmentation, there is still large scope for further algorithmic developments due to performance issues related to the high variability of  ...  JA Schnabel and VA Zimmer would like to acknowledge funding from a Wellcome Trust IEH Award (WT 102431), an EPSRC programme grant (EP/P001009/1), and the Wellcome/EPSRC Center for Medical Engineering (  ... 
arXiv:2106.09862v3 fatcat:y7gk5bjqirgotbx3bwfq62rnqy

Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos [article]

Hugo Jair Escalante, Heysem Kaya, Albert Ali Salah, Sergio Escalera, Yagmur Gucluturk, Umut Guclu, Xavier Baro, Isabelle Guyon, Julio Jacques Junior, Meysam Madadi, Stephane Ayache, Evelyne Viegas, Furkan Gurpinar, Achmadnoer Sukma Wicaksana (+3 others)
2019 arXiv   pre-print
Finally, derived from our study, we outline research opportunities that we foresee will be decisive in the near future for the development of the explainable computer vision field.  ...  The final score fusion with RF outperforms weighted fusion in all but one dimension (agreeableness), where the performances are equal.  ...  BU-NKU: Decision Trees for Modality Fusion and Explainable Machine Learning The BU-NKU system is based on audio, video, and scene features.  ... 
arXiv:1802.00745v3 fatcat:o22jgp5n4ra7fghtpbf42ikde4

Unbiased Directed Object Attention Graph for Object Navigation [article]

Ronghao Dang, Zhuofan Shi, Liuyi Wang, Zongtao He, Chengju Liu, Qijun Chen
2022 arXiv   pre-print
[8] utilize cross-modality knowledge reasoning (CKR) to apply an external knowledge graph in the agent's navigation. Zhang et al.  ...  , and the ability to map the environment to reality.  ... 
arXiv:2204.04421v2 fatcat:b3d6cdgbb5ckzepc2mvm2ghwm4

Visual Analysis in Traffic & Re-identification [article]

Andreas Møgelmose
2015 Ph.d.-serien for Det Teknisk-Naturvidenskabelige Fakultet, Aalborg Universitet  
Eshed Ohn-Bar for their comments.  ...  The authors would also like to acknowledgment Cassa di Risparmio di Parma e Piacenza for funding the test platform used for this work.  ...  "A Decision Fusion and Reasoning Module for a Traffic Sign Recognition System".  ... 
doi:10.5278/vbn.phd.engsci.00026 fatcat:taivrerts5debi734ddeeaq244

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.  ...  In this paper, we present state-of-the-art computing systems for autonomous driving, including seven performance metrics and nine key technologies, followed by twelve challenges to realize autonomous driving  ...  Localization is responsible for finding ego-position relative to a map [105] . The mapping constructs multi-layer high definition (HD) maps [106] for path planning.  ... 
arXiv:2009.14349v3 fatcat:xmo6mxucizf33hu2n2ddoy4xsy

Breast compression parameters among women imaged with full field digital mammography and breast tomosynthesis in BreastScreen Norway

N. Moshina, Solveig Hofvind, Gunvor Waade, Åsne Holen, Berit Hanestad, Sofie Sebuødegård, K. Pedersen, Elizabeth A. Krupinski
2018 14th International Workshop on Breast Imaging (IWBI 2018)  
positive rate for detecting a true change in uptake).  ...  Ten-fold cross validation was used for model selection.  ...  The aim of this paper is to evaluate temporal breast density changes using density maps, provided by the commercial software Volpara.  ... 
doi:10.1117/12.2317918 dblp:conf/iwbi/WadeHHSMPH18 fatcat:gyksxd5b2jf4jpntucqs5zjc5i

A Survey of Localization Methods for Autonomous Vehicles in Highway Scenarios

Johann Laconte, Abderrahim Kasmi, Romuald Aufrère, Maxime Vaidis, Roland Chapuis
2021 Sensors  
For this purpose, the vehicle needs to be able to take into account the information from several sensors and fuse them with data coming from road maps.  ...  In this survey, we introduce a taxonomy of the localization methods for autonomous vehicles in highway scenarios.  ...  [31] characterize a CRF model for Map-Matching. To verify the effectiveness of the model, the authors performed the Map-Matching on a dataset from Shanghai taxis.  ... 
doi:10.3390/s22010247 pmid:35009790 pmcid:PMC8749843 fatcat:aqd7iddh2za4dbmeyeyxl3kyme
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