Poverty in India is a complex issue with multiple causes. This paper mainly focuses on three of the main causes for poverty: Education, Unemployment and Consumer Price Index. This study makes use of data received from...
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Understanding and integrating physiological data collected from wearable sensors in remote patient monitoring (RPM) is challenging. Data streams may be interrupted due to the sensor's sensitivity, movement, and el...
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ISBN:
(纸本)9798350336672
Understanding and integrating physiological data collected from wearable sensors in remote patient monitoring (RPM) is challenging. Data streams may be interrupted due to the sensor's sensitivity, movement, and electromagnetic interference leading to inconsistent, missing, and inaccurate data. Existing approaches to summarize data flows into a single score such as the traditional Modified early warning score (MEWS) is limited. Data visualization approaches have the potential to address this challenge, but few studies have focused on visualization of RPM streams. The study presents a transformation of observed raw RPM physiological data into parameters identified as trust, frequency, slope, and trend. This facilitated visualization and enabled automated assessments of prioritized alerts. Experimental results have shown that the transformations led to the prioritization of clinically significant conditions, and improved visualization has the potential to better support clinical decisions compared with traditional MEWS.
Face relighting is the challenging task of estimating the illumination cast on portrait images by a light source varying in both position and intensity. As shadows are an important aspect of relighting, many prior wor...
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ISBN:
(纸本)9798350318920;9798350318937
Face relighting is the challenging task of estimating the illumination cast on portrait images by a light source varying in both position and intensity. As shadows are an important aspect of relighting, many prior works focus on estimating accurate shadows using either a shadow mask or face geometry. While these work well, the rendered images do not look aesthetic/photo-realistic. We propose a novel method that combines the features from attention maps at higher resolutions with the lighting information to estimate aesthetic relit images with accurate shadows. We created a new relighting dataset using a synthetic One-Light-At-a-Time (OLAT) lighting rig in Blender software that captures most of the variations encountered in face relighting. Through extensive experimental validation, we show that the performance of our model is better than the current state-of-art face relighting models despite training on a significantly smaller dataset of only synthetic images. We also demonstrate unsupervised domain adaptation from synthetic to real images. We show that our model is able to adapt very well to significantly different out-of-training light source positions.
作者：
Hu, LiAlibaba Grp
Inst Intelligent Comp Hangzhou Peoples R China
Character Animation aims to generating character videos from still images through driving signals. Currently, diffusion models have become the mainstream in visual generation research, owing to their robust generative...
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ISBN:
(数字)9798350353006
ISBN:
(纸本)9798350353013;9798350353006
Character Animation aims to generating character videos from still images through driving signals. Currently, diffusion models have become the mainstream in visual generation research, owing to their robust generative capabilities. However, challenges persist in the realm of image-to-video, especially in character animation, where temporally maintaining consistency with detailed information from character remains a formidable problem. In this paper, we leverage the power of diffusion models and propose a novel framework tailored for character animation. To preserve consistency of intricate appearance features from reference image, we design ReferenceNet to merge detail features via spatial attention. To ensure controllability and continuity, we introduce an efficient pose guider to direct character's movements and employ an effective temporal modeling approach to ensure smooth inter-frame transitions between video frames. By expanding the training data, our approach can animate arbitrary characters, yielding superior results in character animation compared to other image-to-video methods. Furthermore, we evaluate our method on image animation benchmarks, achieving state-of-the-art results.
Accurately perceiving the depth of transparent objects is crucial for modern automation and robotics but is challenging due to their optical properties. To address this challenge, This paper proposes an MFAU-Net-based...
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SmartSort Visualizer, integrating Data Structures and Algorithms with Java, offers a tool for sorting and algorithm analysis. Users can choose from various algorithms, including Bubble Sort, Selection Sort, Insertion ...
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Binary information trees are key visualization and evaluation tools, particularly during the passing of algorithms and synthesizing designs. This paper is an interactive tool for producing binary information trees ove...
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This paper attempts to visualize stress by analyzing data collected from an IoT device called "MindScale™."The healthcare field, including stress visualization, will be revolutionized by Industry 4.0, focusi...
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As the complexity and scale of project management continue to grow, traditional project management methods struggle to meet the demands for efficiency and transparency. Intelligent project management leverages modern ...
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With the rapid advancement of information technology, various industries are generating vast amounts of complex data, making their efficient processing and utilization an urgent issue. Traditional data analysis method...
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