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 Health indexes are useful tools for monitoring the health condition of a population and can be used to guide the healthcare policy of governments. However, most health indexes are
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 Medical image processing algorithms have traditionally focused on a specific problem or disease per modality. This approach has continued with the wide-spread adoption of deep learning in the last
Universal multi-modal deep network for classification and segmentation of medical images 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
