We describe a biologically plausible model of dynamic recognition and learning in the visual cortex based on the statistical theory of Kalman filtering from optimal control theory. The model utilizes a hierarchical network whose successive levels implement Kalman filters operating over successively larger spatial and temporal scales. Each hierarchical level in the network predicts the current v...

Studies related to vegetation dynamics in heterogeneous landscapes often require Normalized Difference Vegetation Index (NDVI) datasets with both high spatial resolution and frequent coverage, which cannot be satisfied by a single sensor due to technical limitations. In this study, we propose a new method called NDVI-Bayesian Spatiotemporal Fusion Model (NDVI-BSFM) for accurately and effectivel...

Short-term forecasts of air pollution levels in big cities are now reported in newspapers and other media outlets. Studies indicate that even short-term exposure to high levels of an air pollutant called atmospheric particulate matter can lead to long-term health effects. Data are typically observed at fixed monitoring stations throughout a study region of interest at different time points. Sta...

The interpretation of remotely sensed images in a spatiotemporal context is becoming a valuable research topic. It helps predicting future trends and behaviors, allowing remotely sensed users to make proactive and knowledgedriven decisions. These decisions are useful for urban sprawl prevention, estimation of changes regarding productivity, and planting status of agricultural products, etc. How...

Lipreading is the task of decoding text from the movement of a speaker’s mouth. Traditional approaches separated the problem into two stages: designing or learning visual features, and prediction. More recent deep lipreading approaches are end-to-end trainable (Wand et al., 2016; Chung & Zisserman, 2016a). All existing works, however, perform only word classification, not sentence-level sequenc...

“A Bayesian kriged Kalman model for short-term forecasting of air pollution levels” (2005) Sujit K. Sahu and Kanti V. Mardia http://www.blackwell-synergy.com/links/doi/10.1111/j.14679876.2005.00480.x/pdf?cookieSet=1 Shor t-term forecasts of air pollution levels in big cities are now repor ted in newspapers and other media outlets. Studies indicate that even shor t-term exposure to high levels o...

Introduction: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. Methods: We used Poisson spa...

Floods have brought a great threat to the life and property of human beings. Under premise strengthening flood control engineering measures following strategic thinking sustainable development, many achievements been made in forecasting recently. However, due complexity traditional lumped model distributed model, hydrologic parameter calibration process is full difficulties, leading long develo...