Deep LearningOntologySemantic Search2022 Little Lion ScientificDeep learning is a predominant branch in machine learning, which is inspired by the operation of the human biological brain in processing information and capturing insights. Deep learning uses several layers of neurons; each layer of neurons...
Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. DL allows analysis of unstructured data and automated identification of features. The recent development of large...
Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. DL allows analysis of unstructured data and automated identification of features. The recent development of large...
Recent advances and applications of deep learning, electroencephalography, and modern analysis techniques in screening, evaluation, and mechanistic analysi... Recent advances and applications of deep learning, electroencephalography, and modern analysis techniques in screening, evaluation, and mechanistic ...
Learning with images and their classification, segmentation, localization, annotation, and abnormally detection is one of the current challenging and exciting task for the researchers. Recently deep learning techniques give excellent performance in Object Detection, Speech Recognition, Abnormality Detection, ...
Deep learning has received extensive research interest in developing new medical image processing algorithms, and deep learning based models have been remarkably successful in a variety of medical imaging tasks to support disease detection and diagnosis. Despite the success, the further improvement of dee...
^S. Chilamkurthy, “Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study,” The Lancet, vol. 392, no. 10162, pp. 2388–2396, 2018. ^H. Ye, F. Gao, Y. Yin et al., “Precise diagnosis of intracranial hemorrhage and subtypes using a thre...
Relaxing the Core FL Assumptions: Applications to Emerging Settings and Scenarios 第二章开始这里就谈及“放宽联邦学习核心假设”,这个联邦学习的核心前提条件(核心假设)到底是什么?我觉得文章里应该是指的谷歌Gboard mobile keyboard项目的场景和设定,也就是cross-device跨设备的联邦学习。基于这个核心假设,文中又提...
Dialogue systems are a popular natural language processing (NLP) task as it is promising in real-life applications. It is also a complicated task since man
Deep learning for named entity recognition: a survey Named entity recognition (NER) aims to identify the required entities and their types from unstructured text, which can be utilized for the construction of... Z Hu,W Hou,X Liu - 《Neural Computing & Applications》 被引量: 0发表: 2024年...