Abstract: Network traffic classification solutions have increasingly adopted complex models to improve performance. Yet, we show that a simple 1-nearest neighbor classifier-using only a compact ...

Learn the concept of in-context learning and why it’s a breakthrough for large language models. Clear and beginner-friendly explanation. #InContextLearning #DeepLearning #LLMs Supreme Court Deals ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...

Tensors are the fundamental building blocks in deep learning and neural networks. But what exactly are tensors, and why are they so important? In this video, we break down the concept of tensors in ...

The Learning Household, a new book by Ken Bain and Marsha Marshall Bain, truly resonated with me because it affirms something I have always believed as a parent: the home should be a place where ...

Pod numbers are important for assessing soybean yield. How to simplify the traditional manual process and determine the pod number phenotype of soybean maturity more quickly and accurately is an ...

Abstract: Due to the limitations of collection conditions and costs, public brain network datasets generally combine data from multiple sites. However, the difference among multi-source data collected ...

When most people think of the term "accent wall", much of what comes to mind are bright colors, bold patterns, and an intentional dissonance from the surrounding room. But there is plenty of inspo out ...

Accurate and timely detection of diabetic retinopathy (DR) is crucial for managing its progression and improving patient outcomes. However, developing algorithms to analyze complex fundus images ...