Semantic segmentation is the task of classifying images on a pixel level 📷.
It has multiple use-cases in self-driving cars 🚓, medicine 🏥, makeup tools and photography etc.
In this article, I cover various techniques which can be used to implement semantic segmentation for images, videos, point clouds and also cover loss functions, metrics, datasets and annotation tools involved
Researchers from DeepMind and Google recently conducted a thorough empirical study of hyperparameter selection for offline RL, aiming to identify and develop more reliable and effective approaches.
The researchers’ workflow for applying offline hyperparameter selection can be summarized as follows:
Use several different hyperparameter settings for offline RL policies training.
外围体育投注Summarize each policy’s performance by scalar statistics to execute in the real environment.
外围体育投注Pick the top k best policies according to the summary statistics.
Here is a quick read:
The paper Hyperparameter Selection for Offline Reinforcement Learning is on .