Jonathan Middleton,Jaakko Hakulinen,Katariina Tiitinen et al.
Jonathan Middleton et al.
The process of transforming data into sounds for auditory display provides unique user experiences and new perspectives for analyzing and interpreting data. A research study for data transformation to sounds based on musical elements, calle...
Proliferation of atmospheric datasets can hinder policy making: a data blending technique offers a solution [0.03%]
大气数据集的激增可能阻碍政策制定：一种数据融合技术提供了解决方案
Hamish Steptoe,Theo Economou
Hamish Steptoe
The proliferation of atmospheric datasets is a key outcome from the continued development and advancement of our collective scientific understanding. Yet often datasets describing ostensibly identical processes or atmospheric variables prov...
Artificial intelligence research strategy of the United States: critical assessment and policy recommendations [0.03%]
美国人工职能研究战略：批评与政策建议
Furkan Gursoy,Ioannis A Kakadiaris
Furkan Gursoy
The foundations of Artificial Intelligence (AI), a field whose applications are of great use and concern for society, can be traced back to the early years of the second half of the 20th century. Since then, the field has seen increased res...
Kernel-wise difference minimization for convolutional neural network compression in metaverse [0.03%]
元宇宙中基于卷积神经网络内核差分最小化的模型压缩方法
Yi-Ting Chang
Yi-Ting Chang
Convolutional neural networks have achieved remarkable success in computer vision research. However, to further improve their performance, network models have become increasingly complex and require more memory and computational resources. ...
Arrival times by Recurrent Neural Network for induced seismic events from a permanent network [0.03%]
基于永久地震台网的诱发地震事件递归神经网络到时挑选研究
Petr Kolar,Umair Bin Waheed,Leo Eisner et al.
Petr Kolar et al.
We have developed a Recurrent Neural Network (RNN)-based phase picker for data obtained from a local seismic monitoring array specifically designated for induced seismicity analysis. The proposed algorithm was rigorously tested using real-w...
Leveraging extreme scale analytics, AI and digital twins for maritime digitalization: the VesselAI architecture [0.03%]
基于极端规模分析、人工智能和数字孪生的海上业务数字化：VesselAI架构
Loukas Ilias,Giannis Tsapelas,Panagiotis Kapsalis et al.
Loukas Ilias et al.
The modern maritime industry is producing data at an unprecedented rate. The capturing and processing of such data is integral to create added value for maritime companies and other maritime stakeholders, but their true potential can only b...
Ki-Cook: clustering multimodal cooking representations through knowledge-infused learning [0.03%]
知识增强学习的多模态烹饪表示聚类：Ki-Cook方法
Revathy Venkataramanan,Swati Padhee,Saini Rohan Rao et al.
Revathy Venkataramanan et al.
Cross-modal recipe retrieval has gained prominence due to its ability to retrieve a text representation given an image representation and vice versa. Clustering these recipe representations based on similarity is essential to retrieve relev...
Too much information is no information: how machine learning and feature selection could help in understanding the motor control of pointing [0.03%]
信息过载即无信息：机器学习和特征选择在理解指控行为的运动控制中的作用及其潜在帮助
Elizabeth Thomas,Ferid Ben Ali,Arvind Tolambiya et al.
Elizabeth Thomas et al.
The aim of this study was to develop the use of Machine Learning techniques as a means of multivariate analysis in studies of motor control. These studies generate a huge amount of data, the analysis of which continues to be largely univari...
Assessment of geothermal resource potential in Changbaishan utilizing high-precision gravity-based man-machine interactive inversion technology [0.03%]
基于高精度重力的人机交互正反演技术在长白山地热资源潜力评价中的应用研究
Zhi-He Xu,Ji-Yi Jiang,Guan-Wen Gu et al.
Zhi-He Xu et al.
As one of the clean energy sources, geothermal resources have no negative impact in changing the climate. However, the accurate assessment and precise identification of the potential geothermal resource is still complex and dynamic. In this...
Ieuan Clay,Valeria De Luca,Akane Sano
Ieuan Clay