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Learning Dynamics and Heterogeneity of Spatial-Temporal Graph Data for Traffic Forecasting
IEEE Transactions on Knowledge and Data Engineering, 2021Accurate traffic forecasting is critical in improving safety, stability, and efficiency of intelligent transportation systems. Despite years of studies, accurate traffic prediction still faces the following challenges, including modeling the dynamics of ...
Shengna Guo +4 more
semanticscholar +1 more source
Computer Vision and Pattern Recognition, 2023
With the springing up of face synthesis techniques, it is prominent in need to develop powerful face forgery detection methods due to security concerns.
Yuan Wang +4 more
semanticscholar +1 more source
With the springing up of face synthesis techniques, it is prominent in need to develop powerful face forgery detection methods due to security concerns.
Yuan Wang +4 more
semanticscholar +1 more source
Transformers for EEG-Based Emotion Recognition: A Hierarchical Spatial Information Learning Model
IEEE Sensors Journal, 2022The spatial information of Electroencephalography (EEG) is essential for emotion recognition model to learn discriminative feature. The convolutional networks and recurrent networks are the conventional choices to learn the complex spatial dependencies ...
Zhe Wang +4 more
semanticscholar +1 more source
Neural Processing Letters, 2006
Neurons are electrically active structures determined by the evolution of ion-specific pumps and channels that allow the transfer of charges under the influence of electric fields and concentration gradients. Extensive studies of spike timing of neurons and the relationship to learning exist. However, the properties of spatial activations during action
Dorian Aur, Mandar S. Jog
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Neurons are electrically active structures determined by the evolution of ion-specific pumps and channels that allow the transfer of charges under the influence of electric fields and concentration gradients. Extensive studies of spike timing of neurons and the relationship to learning exist. However, the properties of spatial activations during action
Dorian Aur, Mandar S. Jog
openaire +1 more source
2006
The scope of research described in this contribution is to verify if the performance in a spatial reconstruction task is determined from mechanisms of visuo-spatial memory and from the characteristics of the subject, like the age and the sex, rather than from those of the environment, like landmarks or elements contained within it (in turn ...
LAI B. +2 more
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The scope of research described in this contribution is to verify if the performance in a spatial reconstruction task is determined from mechanisms of visuo-spatial memory and from the characteristics of the subject, like the age and the sex, rather than from those of the environment, like landmarks or elements contained within it (in turn ...
LAI B. +2 more
openaire +1 more source
Proceedings of the 2nd international conference on Computer graphics, virtual Reality, visualisation and interaction in Africa, 2003
This paper presents the novel idea of using the cognitive mapping process to teach relationships between data items, called the spatial learning method. To investigate the feasibility of the method, a VE based on a data set was created. Three studies using this VE were run concurrently on a single set of 40 participants.
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This paper presents the novel idea of using the cognitive mapping process to teach relationships between data items, called the spatial learning method. To investigate the feasibility of the method, a VE based on a data set was created. Three studies using this VE were run concurrently on a single set of 40 participants.
openaire +1 more source
Efficiently Learning Spatial Indices
2023 IEEE 39th International Conference on Data Engineering (ICDE), 2023Learned indices can leverage the high prediction accuracy and efficiency of modern deep learning techniques. They are capable of delivering better query performance than traditional indices over one-dimensional data. Recent studies demonstrate that we can also achieve query-efficient learned in-dices for spatial data by partitioning and subsequently ...
Liu, Guanli +4 more
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Learning anatomy enhances spatial ability
Anatomical Sciences Education, 2013Spatial ability is an important factor in learning anatomy. Students with high scores on a mental rotation test (MRT) systematically score higher on anatomy examinations. This study aims to investigate if learning anatomy also oppositely improves the MRTâscore.
Vorstenbosch, M.A.T.M. +5 more
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2017
This chapter introduces a novel ensemble learning framework called spatial ensemble, which is used to classify heterogeneous spatial data with class ambiguity. Class ambiguity refers to the phenomenon whereby samples with similar features belong to different classes at different locations (e.g., spectral confusion between different thematic classes in ...
Zhe Jiang, Shashi Shekhar
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This chapter introduces a novel ensemble learning framework called spatial ensemble, which is used to classify heterogeneous spatial data with class ambiguity. Class ambiguity refers to the phenomenon whereby samples with similar features belong to different classes at different locations (e.g., spectral confusion between different thematic classes in ...
Zhe Jiang, Shashi Shekhar
openaire +1 more source
2021
Machine Learning has a plethora of applications in computer science and every-day life, spanning from image processing to video game AI. The usage of machine learning models, such as Artificial Neural Networks, has yielded significant benefits in the execution of tasks, that would otherwise be impractical via conventional algorithms. In this thesis, we
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Machine Learning has a plethora of applications in computer science and every-day life, spanning from image processing to video game AI. The usage of machine learning models, such as Artificial Neural Networks, has yielded significant benefits in the execution of tasks, that would otherwise be impractical via conventional algorithms. In this thesis, we
openaire +2 more sources