Detroit news networks

Sampson Davis Tells Dr. Sampson Davis tells Dr. Oz about the various things he's had to remove from people's bodies in the E. Kenny Banh Tells Dr. Kenny Banh tells Dr. Oz about one patient who thought a five-foot-tapeworm was his intestines coming out of his body. Oz some of the most shocking items that you've actually seen stuck inside somebody. Family Feud Question of the Day! First Forecast Weather October 24, today Clouds increase then rain moves in from the south.

First Forecast Weather October 23, tonight Frost Advisory from 1 am through 9 am and partly cloudy skies. A new study is how Hasani et al. Researchers observe that NCPs performing lane keeping tasks continue to pay attention to road horizons and boundaries when making driving decisions, much like humans are driving a car. The other neural networks they studied were not always focused on the road.

They found that when the NCP was trained to complete a task, the network interacted with the environment and learned to explain the intervention. In essence, the network recognizes whether its output has been altered by a particular intervention and correlates cause and effect.

During training, the network runs forward to produce output and then runs backwards to fix the error. Researchers have observed that NCP correlates cause and effect between forward and backward modes.

This allows the network to focus very much on the true causal structure of the task. Hasani and his colleagues did not have to impose additional constraints on the system or perform any special settings on the NCP to learn this causal relationship. They tested NCP through a series of simulations of autonomous drones performing navigation tasks. Each drone navigated using input from one camera. The drone was responsible for moving to the target object, tracking the moving target, or tracking a series of markers in different environments such as Redwood Forest and neighborhoods.

They also traveled under a variety of weather conditions, including sunny weather, heavy rain, and fog. Researchers have found that on sunny days, NCPs work on simple tasks like any other network, but outperform all networks on more difficult tasks, such as chasing moving objects in a storm. I did. Their results show that NCP allows autonomous drones to navigate successfully even in changing conditions, such as sunny landscapes with sudden fog.