Results 311 to 320 of about 5,112,987 (375)
Some of the next articles are maybe not open access.
A survey of visual analytics for Explainable Artificial Intelligence methods
Computers & graphics, 2021Deep learning (DL) models have achieved impressive performance in various domains such as medicine, finance, and autonomous vehicle systems with advances in computing power and technologies.
Gulsum Alicioglu, Bo Sun
semanticscholar +1 more source
Visual Analytics for Machine Learning: A Data Perspective Survey
IEEE Transactions on Visualization and Computer Graphics, 2023The past decade has witnessed a plethora of works that leverage the power of visualization (VIS) to interpret machine learning (ML) models. The corresponding research topic, VIS4ML, keeps growing at a fast pace.
Junpeng Wang, Shixia Liu, Wei Zhang
semanticscholar +1 more source
IEEE Computer Graphics and Applications, 2004
The information revolution is upon us, and it is guaran-teed to change our lives and the way we conduct our daily business. The fact that we have to deal with not just the size but also the variety and complexity of this in-formation makes it a real challenge to survive the revolu-tion.
Pak Chung, Wong, Jim, Thomas
openaire +2 more sources
The information revolution is upon us, and it is guaran-teed to change our lives and the way we conduct our daily business. The fact that we have to deal with not just the size but also the variety and complexity of this in-formation makes it a real challenge to survive the revolu-tion.
Pak Chung, Wong, Jim, Thomas
openaire +2 more sources
Visual Concept Programming: A Visual Analytics Approach to Injecting Human Intelligence at Scale
IEEE Transactions on Visualization and Computer Graphics, 2022Data-centric AI has emerged as a new research area to systematically engineer the data to land AI models for real-world applications. As a core method for data-centric AI, data programming helps experts inject domain knowledge into data and label data at
Md. Naimul Hoque +4 more
semanticscholar +1 more source
Context-aware image compression optimization for visual analytics offloading
ACM SIGMM Conference on Multimedia Systems, 2022Convolutional Neural Networks (CNN) have given rise to numerous visual analytics applications at the edge of the Internet. The image is typically captured by cameras and then live-streamed to edge servers for analytics due to the prohibitive cost of ...
Bo Chen, Zhisheng Yan, K. Nahrstedt
semanticscholar +1 more source
A General Dynamic Knowledge Distillation Method for Visual Analytics
IEEE Transactions on Image Processing, 2022Existing knowledge distillation (KD) method normally fixes the weight of the teacher network, and uses the knowledge from the teacher network to guide the training of the student network no-ninteractively, thus it is called static knowledge distillation (
Zhigang Tu, Xiangjian Liu, Xuan Xiao
semanticscholar +1 more source
Explaining artificial intelligence with visual analytics in healthcare
WIREs Data Mining Knowl. Discov., 2021To make predictions and explore large datasets, healthcare is increasingly applying advanced algorithms of artificial intelligence. However, to make well‐considered and trustworthy decisions, healthcare professionals require ways to gain insights in ...
Jeroen Ooge, Gregor Stiglic, K. Verbert
semanticscholar +1 more source
1st Europe Summer School on Data Science - SummerSchool '17, 2017
Visual analytics aims to combine the strengths of human and computer data processing. Visualization, whereby humans and computers cooperate through graphics, is the means through which this is achieved. Sophisticated synergies are required for analyzing spatio-temporal data and solving spatio-temporal problems.
Natalia Andrienko, Gennady Andrienko
openaire +1 more source
Visual analytics aims to combine the strengths of human and computer data processing. Visualization, whereby humans and computers cooperate through graphics, is the means through which this is achieved. Sophisticated synergies are required for analyzing spatio-temporal data and solving spatio-temporal problems.
Natalia Andrienko, Gennady Andrienko
openaire +1 more source
Visual Analytics for RNN-Based Deep Reinforcement Learning
IEEE Transactions on Visualization and Computer Graphics, 2021Deep reinforcement learning (DRL) targets to train an autonomous agent to interact with a pre-defined environment and strives to achieve specific goals through deep neural networks (DNN). Recurrent neural network (RNN) based DRL has demonstrated superior
Junpeng Wang +4 more
semanticscholar +1 more source
LEVA: Using Large Language Models to Enhance Visual Analytics
IEEE Transactions on Visualization and Computer GraphicsVisual analytics supports data analysis tasks within complex domain problems. However, due to the richness of data types, visual designs, and interaction designs, users need to recall and process a significant amount of information when they visually ...
Yuheng Zhao +7 more
semanticscholar +1 more source