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Chapter
Demographic Differences and Biases in Affect Evoked by Visual Features
Visual stimuli influence our affective state and reactions, subsequently sha** our preferences. These interactions fall within the domain of affective computing research. Furthermore, affective state and emo...
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Chapter
ExpressionFlow: A Microexpression Descriptor for Efficient Recognition
Microexpressions are involuntary facial movements that often reflect a person’s true emotions. Their fleeting nature and subtle shifts, however, make them challenging to detect. Our earlier work, the Facial Dy...
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Book
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Chapter
High-Speed Joint Learning of Action Units and Facial Expressions
Facial expressions serve as a crucial facet of human behavior, offering a wealth of social and emotional cues. Despite their significance, achieving real-time, accurate, and interpretable recognition of facial...
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Article
Open AccessA resource scheduling method for cloud data centers based on thermal management
With the rapid growth of cloud computing services, the high energy consumption of cloud data centers has become a critical concern of the cloud computing society. While virtual machine (VM) consolidation is of...
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Article
Deep-profiling: a deep neural network model for scholarly Web user profiling
Scholarly big data refer to the rapidly growing scholarly source of information, including a large number of authors, papers, and massive scale scholarly networks. Extracting the profile attributes for Web use...
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Article
HCIndex: a Hilbert-Curve-based clustering index for efficient multi-dimensional queries for cloud storage systems
With the rapid development of the Internet of Things and cloud computing, HBase has become a good choice for massive data storage, and is efficient in reading and writing data. However, HBase is not supportive...
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Chapter and Conference Paper
Dyslexia Data Consortium Repository: A Data Sharing and Delivery Platform for Research
Specific learning disability of reading, or dyslexia, affects 5–17% of the population in the United States. Research on the neurobiology of dyslexia has included studies with relatively small sample sizes acro...
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Chapter and Conference Paper
Enhancing Automatic Placenta Analysis Through Distributional Feature Recomposition in Vision-Language Contrastive Learning
The placenta is a valuable organ that can aid in understanding adverse events during pregnancy and predicting issues post-birth. Manual pathological examination and report generation, however, are laborious an...
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Chapter and Conference Paper
Asymmetry Disentanglement Network for Interpretable Acute Ischemic Stroke Infarct Segmentation in Non-contrast CT Scans
Accurate infarct segmentation in non-contrast CT (NCCT) images is a crucial step toward computer-aided acute ischemic stroke (AIS) assessment. In clinical practice, bilateral symmetric comparison of brain hemi...
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Chapter and Conference Paper
Vision-Language Contrastive Learning Approach to Robust Automatic Placenta Analysis Using Photographic Images
The standard placental examination helps identify adverse pregnancy outcomes but is not scalable since it requires hospital-level equipment and expert knowledge. Although the current supervised learning approa...
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Chapter and Conference Paper
Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation
We present a new encoder-decoder Vision Transformer architecture, Patcher, for medical image segmentation. Unlike standard Vision Transformers, it employs Patcher blocks that segment an image into large patche...
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Chapter and Conference Paper
LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-Weighted MR Images
Diffusion-weighted (DW) magnetic resonance imaging is essential for the diagnosis and treatment of ischemic stroke. DW images (DWIs) are usually acquired in multi-slice settings where lesion areas in two conse...
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Chapter and Conference Paper
Toward Rapid Stroke Diagnosis with Multimodal Deep Learning
Stroke is a challenging disease to diagnose in an emergency room (ER) setting. While an MRI scan is very useful in detecting ischemic stroke, it is usually not available due to space constraint and high cost i...
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Article
ARBEE: Towards Automated Recognition of Bodily Expression of Emotion in the Wild
Humans are arguably innately prepared to comprehend others’ emotional expressions from subtle body movements. If robots or computers can be empowered with this capability, a number of robotic applications beco...
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Chapter and Conference Paper
Panel: Bodily Expressed Emotion Understanding Research: A Multidisciplinary Perspective
Develo** computational methods for bodily expressed emotion understanding can benefit from knowledge and approaches of multiple fields, including computer vision, robotics, psychology/psychiatry, graphics, d...
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Article
A microservice-based architecture for enhancing the user experience in cross-device distributed mashup UIs with multiple forms of interaction
Mobility and continuous connection entail the emergence of heterogeneous devices with multiple forms of interaction. However, it is challenging for developers and corporations to keep up with the devices and p...
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Chapter and Conference Paper
PlacentaNet: Automatic Morphological Characterization of Placenta Photos with Deep Learning
Analysis of the placenta is extremely useful for evaluating health risks of the mother and baby after delivery. In this paper, we tackle the problem of automatic morphological characterization of placentas, in...
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Article
A Linear Time Self-stabilizing Algorithm for Minimal Weakly Connected Dominating Sets
In this paper, we propose a new self-stabilizing algorithm for minimal weakly connected dominating sets (called algorithm $$\mathtt{MW...
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Chapter and Conference Paper
Optimally Storing the User Interaction in Mashup Interfaces Within a Relational Database
Cross-device applications that have user interfaces managed in multiple forms of interaction are prevalent. In particular, component-based (or mashup) applications are growing in popularity due to their easiness ...
