By shifting their focus to the process of learning instead of the product, students are encouraged to develop critical ...

提出一个自适应量化框架，对模型做量化，加速现有超分辨模型的处理速度。 量化敏感度计算：将校准图像输入预训练模型，记录每层激活值，并计算其标准差，作为敏感度。标准差越大，敏感度越高。 位宽因子映射公式： ...

[Notice] This list is not being maintained anymore because of the overwhelming amount of deep learning papers published every day since 2017. A curated list of the most cited deep learning papers ...

Researchers developed a fully integrated photonic processor that can perform all the key computations of a deep neural network on a photonic chip, using light. This advance could improve the speed and ...

MBTL improves deep reinforcement learning by optimizing task selection, boosting sample efficiency and adaptability in ...

In recent years, the evolution of artificial intelligence has brought forth increasingly sophisticated large language models (LLMs). However, training these models remains a complex challenge due to ...

There are two major machine learning approaches: supervised and unsupervised. Supervised learning uses labelled data for tasks like classification, while unsupe ...

The right course can help you unlock the secrets of tarot cards and their meanings. Here are four of the best tarot reading ...

Generative AI's transformative potential in India requires universities to adopt interdisciplinary, inclusive, and ...

Abstract: With the development of deep learning and the increase in the amount of data ... field has not proposed a better general model training solution, and it is difficult to utilize the ...

EEG or electro encephalography is so far one of the most reliable means used to detect the onset of drowsiness and sleep ...

Smart video plays a vital role in increasing public safety such as promoting safe driving practices by monitoring fleet movements to detecting flaws and deviations in a product line to avoid ...