Abstract With the development of society, the number of the archive is increasing day by day. The transmission of the archive is a heavy work that archive staff must face […]
A Full-Automatic Archive Management Robot Read More »
Abstract To guarantee that ships can navigate safely, the International Maritime Organization mandates that all ships navigating internationally must install the automatic identification system (AIS). AIS works in the very
Study of an Evaluation Model for AIS Receiver Sensitivity Measurements Read More »
Abstract Severe flash flood events give very little opportunity for issuing warnings. In this paper, we approach the automated and real-time prediction of river flooding by proposing and evaluating different
An Evolutionary MultiLayer Perceptron Algorithm for Real Time River Flood Prediction Read More »
Abstract In natural clouds, water droplets grow by condensation in a supersaturated environment. Under subsaturatedconditions, water droplets normally keep evaporating until they eventually disappear. In this article, we study the
Corona Discharge-Induced WaterDroplet Growth in Air Read More »
Abstract The relevance to developing the specialized software for automation of the metallographic analysis has been substantiated. The object model of the specialized software for automation of the metallographic analysis
Abstract Magnetomyography (MMG) is the measurement of magnetic signals generated in the skeletal muscle of humans by electrical activities. However, current technologies developed to detect such a tiny magnetic field
Abstract Tesla’s full self-driving (FSD) computer is the world’s first purpose-built computer for the highly demanding workloads of autonomous driving. It is based on a new System on a Chip
Compute Solution for Tesla’s Full Self-Driving Computer Read More »
Abstract Deep learning and convolutional neural network technologies are increasingly used in the problems of analysis, segmentation, and recognition of objects in images. In this article, a convolutional neural network
Wildfire Segmentation on Satellite Images using Deep Learning Read More »
Abstract in this paper, we propose a deep learning approach for the segmentation of body parts in computer tomography (CT) localizer images. Such images pose dif[1]culties in the automatic image
Abstract COVID-19 has caused a global pandemic and become the most urgent threat to the entire world. Tremendous efforts and resources have been invested in developing diagnosis, prognosis and treatment
