Search logs in a timely and efficient manner are an important part of SRE (Site Reliability Engineer). Logs help us solve the problems during our development work. In this paper, we will introduce you a way how to build an efficient logs analysis system based on kafka and Elastic Search. We hope you can learn something through the iteration of the Version and get some inspiration with your own log analysis system.
Traffic sign recognition is an important task in intelligent transportation systems, which can improve road safety and reduce accidents. Algorithms based on deep learning have achieved remarkable results in traffic sign recognition in recent years. In this paper, we build traffic sign recognition algorithms based on ResNet and CNN models, respectively. We evaluate the proposed algorithm on public datasets and compare. We first use the dataset of traffic sign images from Kaggle. And then designed ResNet-based and CNN-based architectures that can effectively capture the complex features of traffic signs. Our experiments show that our ResNet-based model achieves a recognition accuracy of 99% on the test set, and our CNN-based model achieves a recognition accuracy of 98% on the test set. Our proposed approach has the potential to improve traffic safety and can be used in various intelligent transportation systems.
Cancer has become a cause of concern in recent years. Cancer genomics is currently a key research direction in the fields of genetic biology and biomedicine. This paper analyzes 5 different types of cancer genes, such as breast, kidney, colon, lung and prostate through machine learning methods, with the goal of building a robust classification model to identify each type of cancer, which will allow us to identify each type of cancer early, thereby reducing mortality.
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