111 Hits in 7.2 sec

A Trajectory Scoring Tool for Local Anomaly Detection in Maritime Traffic Using Visual Analytics

Fernando H. O. Abreu, Amilcar Soares, Fernando V. Paulovich, Stan Matwin
2021 ISPRS International Journal of Geo-Information  
The amount of interpolation in subtrajectories is displayed together with scores so that users can use both their insight and the trip displayed on the map to determine if the score is reliable.  ...  With the recent increase in the use of sea transportation, the importance of maritime surveillance for detecting unusual vessel behavior related to several illegal activities has also risen.  ...  Each trajectory is segmented based on the spatial regions, creating one subtrajectory for each spatial region.  ... 
doi:10.3390/ijgi10060412 fatcat:ouj5pm62rneptmd2e7zvvopqvq

Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies [article]

Yu Huang, Yue Chen
2020 arXiv   pre-print
Due to the limited space, we focus the analysis on several key areas, i.e. 2D and 3D object detection in perception, depth estimation from cameras, multiple sensor fusion on the data, feature and task  ...  This is a survey of autonomous driving technologies with deep learning methods.  ...  semantics (by joint stereo-LiDAR segmentation) other than texture information and train an AR model to predict future trajectories of traffic participants (vehicles) based on encoder-decoder and LSTM.  ... 
arXiv:2006.06091v3 fatcat:nhdgivmtrzcarp463xzqvnxlwq

An unsupervised approach for semantic place annotation of trajectories based on the prior probability [article]

Junyi Cheng, Xianfeng Zhang, Peng Luo, Jie Huang, Jianfeng Huang
2022 arXiv   pre-print
Herein, we propose an unsupervised method denoted as UPAPP for the semantic place annotation of trajectories using spatiotemporal information.  ...  Most existing methods rely on annotated or external data and require retraining following a change of region, thus preventing their large-scale applications.  ...  Acknowledgments The authors would like to thank Professor Yanwei Chai from the School of Urban and Environmental Sciences, Peking University, for providing the trajectory data and activity logs.  ... 
arXiv:2204.09054v1 fatcat:ad6jsz2tgrhyrisbp7e3wnaeem

Sequential Point Clouds: A Survey [article]

Haiyan Wang, Yingli Tian
2022 arXiv   pre-print
This paper presents an extensive review of the deep learning-based methods for sequential point cloud research including dynamic flow estimation, object detection \& tracking, point cloud segmentation,  ...  However, many of these applications (e.g. autonomous driving and robotic manipulation) are actually based on sequential point clouds (i.e. four dimensions) because the information of the static point cloud  ...  The predicted trajectory and detected objects were associated with Hungarian algorithm in current frame, which can further update trajectory state in 3D Kalman Filter.  ... 
arXiv:2204.09337v2 fatcat:su7fdqd3xja53jg4zikqcpvoaa

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

Abolfazl Razi, Xiwen Chen, Huayu Li, Brendan Russo, Yan Chen, Hongbin Yu
2022 arXiv   pre-print
This processing framework includes several steps, including video enhancement, video stabilization, semantic and incident segmentation, object detection and classification, trajectory extraction, speed  ...  algorithms proposed for each step.  ...  Jason Pacheco, Larry Head, and Junsuo Qu from their thoughtful comments on this paper. Special thanks go to Greg Leeming from Intel for his insightful comments and continued support of this project.  ... 
arXiv:2203.10939v1 fatcat:h4o5zghhhfezncn7luy56yjusm

Deep Reinforcement Learning in Computer Vision: A Comprehensive Survey [article]

Ngan Le, Vidhiwar Singh Rathour, Kashu Yamazaki, Khoa Luu, Marios Savvides
2021 arXiv   pre-print
(i)landmark localization (ii) object detection; (iii) object tracking; (iv) registration on both 2D image and 3D image volumetric data (v) image segmentation; (vi) videos analysis; and (vii) other applications  ...  We start with comprehending the theories of deep learning, reinforcement learning, and deep reinforcement learning.  ...  One trajectory of some finite length τ is called an episode.  ... 
arXiv:2108.11510v1 fatcat:wkkqittwivbx5fpwg3nggcy7cm

Learning-Based Anomaly Detection and Monitoring for Swarm Drone Flights

Hyojung Ahn, Han-Lim Choi, Minguk Kang, SungTae Moon
2019 Applied Sciences  
While the current practice of swarm flight typically relies on the operator's naked eyes to monitor health of the multiple vehicles, this work proposes a machine learning-based framework to enable detection  ...  network classifier with one-dimensional convolution layers followed by fully connected multi-layer perceptron extracts the associated features and distinguishes the anomaly from normal conditions.  ...  Research carried out kernel principal component analysis(KPCA)-based sensor anomaly detection using drone sensor signals [38] .  ... 
doi:10.3390/app9245477 fatcat:ucbyurpbzrhbjbog5vnszzibyi

Table of Contents

2020 2020 IEEE International Conference on Image Processing (ICIP)  
RECOGNITION BASED ON .........................................  ...  TEC-03.4: MDT: UNSUPERVISED MULTI-DOMAIN IMAGE-TO-IMAGE TRANSLATOR ......................................... 598 BASED ON GENERATIVE ADVERSARIAL NETWORKS <H /LQ .HUHQ )X 6KHQJJXL /LQJ 3HQJ &KHQJ 6LFKXDQ  ...  REGULARISATION WITH A ...............................................  ... 
doi:10.1109/icip40778.2020.9191006 fatcat:3fkxl2sjmre2jkryewwo5mlahi

The role of respiration audio in multimodal analysis of movement qualities

Vincenzo Lussu, Radoslaw Niewiadomski, Gualtiero Volpe, Antonio Camurri
2019 Journal on Multimodal User Interfaces  
Next, a set of features, computed from the value of synchronization, is used as an input to machine learning algorithms.  ...  First, the value of synchronization between modalities is computed using the Event Synchronization algorithm.  ...  unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes  ... 
doi:10.1007/s12193-019-00302-1 fatcat:3wa4hnhnsncb7nlzkbhu2ld7em

Big Mobility Data Analytics: Algorithms and Techniques for Efficient Trajectory Clustering

Panagiotis Tampakis
2020 2020 21st IEEE International Conference on Mobile Data Management (MDM)  
Towards this direction, we propose a novel in-DBMS Sampling-based Sub Trajectory Clustering algorithm, namely S 2 T-Clustering, which is incorporated in a real MOD engine over an extensible DBMS (PostgreSQL  ...  Joining trajectory datasets is not only the cornerstone of various trajectory cluster analysis methods, but it is also a significant operation in mobility data analytics with a wide range of applications  ...  The trajectories have the same starting time and similar speed. Figure 2 Figure 2 . 1 : 221 (a) An example of a raw trajectory and (b) an example of linear interpolation.  ... 
doi:10.1109/mdm48529.2020.00055 dblp:conf/mdm/Tampakis20 fatcat:yn3aoqxgtfde7ntdk6b57bcmni

A combined local and global motion estimation and compensation method for cardiac CT

Qiulin Tang, Beshan Chiang, Akinola Akinyemi, Alexander Zamyatin, Bibo Shi, Satoru Nakanishi, Bruce R. Whiting, Christoph Hoeschen
2014 Medical Imaging 2014: Physics of Medical Imaging  
cluster ensembles to combine a set of base unsupervised segmentations into an unified partition of the voxel-based data.  ...  DEI detects small angular deflections in an x-ray beam, and is only sensitive to angular changes in one plane.  ...  Spectra are then automatically classified as one of seven cell-types in prostate tissue in a matter of seconds.  ... 
doi:10.1117/12.2043492 fatcat:fyzpc5m6jbh7fjohqpdmtzkhte

Data Fusion in Earth Observation and the Role of Citizen as a Sensor: A Scoping Review of Applications, Methods and Future Trends

Aikaterini Karagiannopoulou, Athanasia Tsertou, Georgios Tsimiklis, Angelos Amditis
2022 Remote Sensing  
Reviewing the DF models, the majority of the selected articles followed a data-driven method with the traditional algorithms to still hold significant attention.  ...  Approaches such as the "brute-force approach" and the super-resolution models indicate an effective way to overcome the spatio-temporal gaps and the so far reliance on commercial satellite sensors.  ...  In clustering methods, unsupervised algorithms are leveraged, such as Density-based spatial clustering of applications with noise (DBSCAN) and K-means, whereas the third method finds centerlines and notes  ... 
doi:10.3390/rs14051263 fatcat:ffg4ulntnrdrxaknuydepyvelm

2020 Index IEEE Transactions on Industrial Informatics Vol. 16

2020 IEEE Transactions on Industrial Informatics  
End-Edge-Cloud Orchestrated Algorithms, Systems and Applications; TII July 2020 4788-4790 Jiang, J., see Jia, G., 1993-2002 Jiang, J., see Liu, L., 2072-2080 Jiang, J., see Zhang, X., TII Dec. 2020  ...  on Intelligent Clustering in Local Area Industrial IoT Systems; TII June 2020 3697-3707 Jia, S., see Chen, C., 1873-1884 Jia, W., see Wang, T., 2054-2062 Jia, W., see Lian, J., 1343-1351 Jia, W., see  ...  ., +, TII July 2020 4788-4790 Edge detection A Hybrid Demosaicking Algorithm for Area Scan Industrial Camera Based on Fuzzy Edge Strength and Residual Interpolation.  ... 
doi:10.1109/tii.2021.3053362 fatcat:blfvdtsc3fdstnk6qoaazskd3i

3D-ZeF: A 3D Zebrafish Tracking Benchmark Dataset [article]

Malte Pedersen, Joakim Bruslund Haurum, Stefan Hein Bengtson, Thomas B. Moeslund
2020 arXiv   pre-print
The performance of the system is measured with respect to two detectors: a naive approach and a Faster R-CNN based fish head detector. The system reaches a MOTA of up to 77.6%.  ...  In this work we present a novel publicly available stereo based 3D RGB dataset for multi-object zebrafish tracking, called 3D-ZeF.  ...  Zebrafish can change their body pigmentation based on their environment, stress level, and more [23] .  ... 
arXiv:2006.08466v1 fatcat:tzhiwz43gzapjf4ynpo2lmhm4m

A posture sequence learning system for an anthropomorphic robotic hand

Antonio Chella, Haris Džindo, Ignazio Infantino, Irene Macaluso
2004 Robotics and Autonomous Systems  
Work in that area tackles the development of robust algorithms for motor control, motor learning, gesture recognition and visuo-motor integration.  ...  The work is being done with the support of CYCIT, Spanish Research Agency, under the projects: DPI2001-0822 and DPI2002-04286-C2-02 Acknowledgments: Among many people who contributed to the robot system  ...  To segment the human action in high-level operations, a simple algorithm based on changes in the grasping state has been implemented: a new operation is generated whenever a grasped object is released.  ... 
doi:10.1016/j.robot.2004.03.008 fatcat:fefnr5l7gnhnhaca5nw52f3kru
« Previous Showing results 1 — 15 out of 111 results