Results 311 to 317 of about 497,808 (317)

Spatiotemporal-Aware Region Recommendation with Deep Metric Learning

2019
Personalized points of interests (POI) recommendation is an important basis for location-based services. A typical application scenario is to recommend a region with reliable POIs to a user when he/she travels to an unfamiliar area without any background knowledge.
Zhenglu Yang, Jinmao Wei, Hengpeng Xu, Jun Wang, Yao Zhang   +4 more
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Integrating CogPrime with a Compositional Spatiotemporal Deep Learning Network

2014
Many different approaches to “low-level” perception and action processing are possible within the overall CogPrime framework. We discussed several in the previous chapter, all elaborations of the general hierarchical pattern recognition approach.
Nil Geisweiller, Ben Goertzel, Cassio Pennachin   +2 more
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Deep-STEP: A Deep Learning Approach for Spatiotemporal Prediction of Remote Sensing Data

IEEE Geoscience and Remote Sensing Letters, 2016
With the advent of advanced remote sensing technologies in past few decades, acquiring higher resolution satellite images has become easier and cheaper in recent days. However, on the other hand, it has offered a big challenge to the remote sensing community in smart image interpretation from such huge volume of data.
Monidipa Das, Soumya K. Ghosh
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Deep learning in spatiotemporal filtering for super-resolution ultrasound imaging

2019 IEEE International Ultrasonics Symposium (IUS), 2019
Super-resolution ultrasound (SR-US) imaging shows great promise as a clinical technique that can improve ultrasound (US) resolution by an order of magnitude. Current algorithms for SR-US suffer from high complexity and long computation times, precluding real-time imaging.
Kenneth Hoyt, Katherine G. Brown
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Deep learning with applications for spatiotemporal prediction

Spatiotemporal prediction has garnered significant attention for many years. In recent years, deep learning methods have emerged as effective models for spatiotemporal data, surpassing traditional methods in tasks such as data enhancement and prediction. While considerable effort has been dedicated to developing deep learning methods for spatiotemporal
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Gaze Estimation with Spatiotemporal and Multimodal Deep Learning

[spa] El seguimiento ocular tiene una amplia relevancia en diferentes campos relacionados con la investigación, así como en aplicaciones clínicas y de consumo. Los métodos de seguimiento ocular no invasivos, suficientemente precisos y rentables, normalmente basados en cámaras de video, se están volviendo cada vez más accesibles, impulsados por la ...
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Spatiotemporal deep learning

As spatiotemporal sensors become cheaper, spatiotemporal data become more widespread. At the same time, deep learning continues to be the de facto method to extract good representation in multiple applications domains. However, there are several challenges specific to spatiotemporal data.
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