High resolution satellite images are widely used to produce and update a digital map since they became widely available.It is well known that the accuracy of digital map produced from satellite images is decided largely by the accuracy of geometric modelling.However digital maps are made by a series of photogrammetric workflow.Therefore the accurac
A Fast, Open EEG Classification Framework Based on Feature Compression and Channel Ranking
Superior feature extraction, channel selection and classification methods are essential for designing electroencephalography (EEG) classification frameworks.However, the performance of most frameworks is limited by their improper channel selection methods and too specifical design, leading to high computational complexity, non-convergent procedure
Partitioning Convolutional Neural Networks to Maximize the Inference Rate on Constrained IoT Devices
Billions of devices will compose the IoT system in the next few years, generating a huge amount of data.We can use fog computing to process these data, considering that there is the possibility of overloading the network towards the cloud.In this context, deep learning can treat miken pro series 13 these data, but the memory requirements of deep ne