Abstract: Spatial transcriptomic sequencing technology is a powerful tool that combines gene expression data with their physical locations in tissues or organs, providing researchers with ...

In the race to deliver faster, smarter, and more resilient networks, CSP and telco leaders are finding a powerful ally in ...

The Geospatial Professional Network (formerly URISA) is seeking respondents to its 2025 GIS Management Survey. The survey is part of a research project on geographic information system (GIS) ...

Waypoint 33 LLC and Cellular Expert announce a U.S. distribution partnership to expand access to advanced RF modeling and GIS-driven network design solutions Waypoint 33 becomes the official U.S.

Abstract: This paper extends the classical network calculus to spatial scenarios, focusing on wireless networks with differentiated services and varying transmit power levels. Building on a spatial ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

No audio available for this content. The California Spatial Reference Center (CSRC) modernized the California Spatial Reference Network (CSRN) on July 31, 2025. The new California Spatial Reference ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...