To address the trade-off between accuracy and cross-city generalization in traffic flow estimation, a research team from The ...

Some applications are so inherently complicated that it is difficult to dig through the many layers of connected algorithms to expose the parts of the code ripe for optimization. This makes them a ...

Google's open source framework for machine learning and neural networks is fast and flexible, rich in models, and easy to run on CPUs or GPUs What makes Google Google? Arguably it is machine ...

State of the art systems that need to be aware of an environment must relying on sensors, radar, LIDAR, cameras and specialized computing in order to make sense of a chaotic world. Underneath all of ...

Scott Reeves demonstrates the flow graph feature of the Wireshark tool, which can help you check connections between client server, finding timeouts, re-transmitted frames, or dropped connections. I ...

I had great fun writing neural network software in the 90s, and I have been anxious to try creating some using TensorFlow. Google’s machine intelligence framework is the new hotness right now. And ...

Machine learning couldn’t be hotter, with several heavy hitters offering platforms aimed at seasoned data scientists and newcomers interested in working with neural networks. Among the more popular ...

Author’s note: This article shows how to derive circuit gain equations via a signal flow graph. With practice you may be able to write a gain equation by locating signal paths and loops in the ...