Over the last several decades, urban planners and municipalities have sought to identify and better manage the socioeconomic dynamics associated with rapid development in established neighborhoods.
In hopes of providing a better monitoring system for those seeking to mitigate the negative effects of gentrification, ...
Welcome to the Zero to Mastery Learn PyTorch for Deep Learning course, the second best place to learn PyTorch on the internet (the first being the PyTorch documentation). 00 - PyTorch Fundamentals ...
CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
According to DeepLearning.AI (@DeepLearningAI), the new PyTorch for Deep Learning Professional Certificate, led by Laurence Moroney, provides in-depth, practical training on building, optimizing, and ...
Artificial Intelligence systems powered by deep learning are changing how we work, communicate, and make decisions. If we want these technologies to serve society responsibly, tomorrow’s citizens need ...
This study introduces Popnet, a deep learning model for forecasting 1 km-gridded populations, integrating U-Net, ConvLSTM, a Spatial Autocorrelation module and deep ensemble methods. Using spatial ...
Abstract: Functional and technical requirements for the interfaces between algorithms and learning frameworks (including the interfaces provided by training frameworks), and between algorithms and ...
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