Context-aware deep learning enables high-efficacy localization of high concentration microbubbles for super-resolution ultrasound localization microscopyMICROBUBBLESDEEP learningMICROBUBBLE diagnosisMICROSCOPYCOMPUTER-assisted image analysis (Medicine)ULTRASONIC imaging...
Learning a Context-Aware Environmental Residual Correlation Filter via Deep Convolution Features for Visual Object Tracking Visual tracking has become widespread in swarm robots for intelligent video surveillance, navigation, and autonomous vehicles due to the development of mac... YH Joo - 《Mathematics...
针对问题①,作者提出了Multi-Scale Context-Aware Network(MSCAN),如下图,MSCAN每个卷积层都采用了不同感受野的空洞卷积核,再级联为该层的输出,感知不同大小的区域特征。针对问题②,作者提出了Spatial Transform Networks(STN),用于定位行人的不同区域。 Proposed Method (1)Multi-scale Context-aware Network: MSC...
Here, we introduce a deep learning approach based solely on a geometric transformer of atomic coordinates and element names that predicts protein sequences from backbone scaffolds aware of the restraints imposed by diverse molecular environments. To validate the method, we show that it can produce ...
Recently, Internet of Things (IoTs) influences every aspect of human daily lives through intelligent systems as healthcare, traffic management, and smart building. These IoTs systems depend on contextualization of collecting data through context aware system to gain knowledge by using context reasoning...
(Fig.1a). Altogether, Riboformer is an end-to-end tool that facilitates the standardization and interpretation of ribosome profiling datasets, and our results demonstrate the potential of context-aware deep learning models that capture the complex dynamics of biological processes subject to variations ...
Recently, 3D object detection technology based on point clouds has developed rapidly. However, too few points of distant and occluded objects are scanned b
Clinical Context–Aware Biomedical Text Summarization Using Deep Neural Network: Model Development and Validation Background: Automatic text summarization (ATS) enables users to retrieve meaningful evidence from big data of biomedical repositories to make complex clini... M Afzal - 《Journal of Medical ...
The context-aware system is compared with the deep learning baseline in terms of data retrieval time, time consumed to generate concepts, data size consumed to generate such concepts, and complexity analysis of both algorithms. The remainder of the paper is organized as follows. In Section 2, ...
T0 - Multitask Prompted Training Enables Zero-Shot Task Generalization OPT - Open Pre-trained Transformer Language Models. UL2 - a unified framework for pretraining models that are universally effective across datasets and setups. GLM- GLM is a General Language Model pretrained with an autoregress...