Results 21 to 30 of about 9,392,941 (233)
On Optimal Multi-Sensor Network Configuration for 3D Registration [PDF]
Journal of Sensor and Actuator Networks, 2015 Multi-sensor networks provide complementary information for various taskslike object detection, movement analysis and tracking. One of the important ingredientsfor efficient multi-sensor network actualization is the optimal configuration of sensors.In this work, we consider the problem of optimal configuration of a network of coupledcamera-inertial ...
Hadi Aliakbarpour +2 more
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MuSLi: A multi sensor LiDAR detection for C-V2X networks
Computer Networks, 2023 Obstacle detection is a tool adopted in vehicular safety applications, aiming to detect a moving obstacle in an area of interest with the highest accuracy. Different sensors are used for this aim, such as LiDAR devices mounted on board of a vehicle that capture images of the surrounding environment.
Romeo Giuliano +5 more
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Multi-Sensor Lane Finding in Urban Road Networks [PDF]
Robotics: Science and Systems IV, 2008 This paper describes a system for detecting and estimating the properties of multiple travel lanes in an urban road network from calibrated video imagery and laser range data acquired by a moving vehicle. The system operates in several stages on multiple processors, fusing detected road markings, obstacles, and curbs into a stable non-parametric ...
Albert Huang +4 more
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Multi-sensor based strategy learning with deep reinforcement learning for unmanned ground vehicle
International Journal of Intelligent Networks, 2023 As intelligent Unmanned Ground Vehicles (UGVs) find broader applications in areas such as transportation and logistics. The fusion of multiple sensors becomes crucial, since it not only amplifies UGV perception in dynamic scenarios but also underpins ...
Mingyu Luo
doaj +1 more source
Observable Degree Analysis for Multi-Sensor Fusion System
Sensors, 2018 Multi-sensor fusion system has many advantages, such as reduce error and improve filtering accuracy. The observability of the system state is an important index to test the convergence accuracy and speed of the designed Kalman filter.
Zhentao Hu +3 more
doaj +1 more source
Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2021 Nowadays, multi-sensor technologies are applied in many fields, e.g., Health Care (HC), Human Activity Recognition (HAR), and Industrial Control System (ICS). These sensors can generate a substantial amount of multivariate time-series data.
Yu-xin Zhang +3 more
semanticscholar +1 more source
Open Networks: Generalized Multi-Sensor Characterization [PDF]
2006 9th International Conference on Information Fusion, 2006 This paper examines issues in characterizing the performance of information sources as necessary for data fusion and coordination in a net-centric environment. In many practical applications, interacting agents have various degrees ? and possibly time-varying degrees ?
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On the possibility of conditional adversarial networks for multi-sensor image matching [PDF]
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017 A major research area in remote sensing is the problem of multi-sensor data fusion. Especially the combination of images acquired by different sensor types, e.g. active and passive, is a difficult task. Over the last years deep learning methods have proven their high potential for remote sensing applications.
Merkle, Nina +3 more
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Multi-modal sensor networks for more effective sensing in Irish coastal and freshwater environments [PDF]
, 2012 The world’s oceans represent a vital resource to global economies and there exists huge economic opportunity that remains unexploited. However along with this huge potential there rests a responsibility into understanding the effects various ...
O'Connor, Noel E. +3 more
core +3 more sources
Bert-GCN: multi-sensors network prediction
ITM Web of Conferences, 2022 With the application of neural network technologies such as GCN and GRU in sensor networks, the accuracy and robustness of multi-sensor prediction have been greatly improved. GCN effectively uses the spatial characteristics of the sensor network, and GRU effectively uses the temporal characteristics of the sensor network, so the PROPOSED T-GCN model ...
Liu Peng +3 more
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