Academic Articles & Research Papers

Microstructure-based variational deep material networks for robust uncertainty quantification in materials digital twins

Abstract Aleatoric uncertainties – irremovable variability in microstructure morphology, constituent behavior, and processing conditions – pose a major challenge to developing uncertainty-robust digital twins. We introduce the Variational D...

Large datasets of water vapor sorption, mass diffusion immersed in water, hygroscopic expansion and mechanical properties of flax fibre/shape memory epoxy hygromorph composites

This data article presents four experimental sets of results related to flax fibre composites with epoxy shape memory polymer matrix: water vapor absorption, mass diffusion immersed in water, hygroscopic expansion, mechanical properties. Th...

Performance, Recalibration, and Implementation of In-Hospital Mortality Prediction Models for Myocardial Infarction.

Developing Clinical Risk Prediction Models for Worsening Heart Failure Events and Death by Left Ventricular Ejection Fraction

Background There is a need to develop electronic health record–based predictive models for worsening heart failure (WHF) events across clinical settings and across the spectrum of left ventricular ejection fraction (LVEF). Methods and Resul...

Enhancing educational semantic retrieval through dual objective fine tuning of open source embedding models

Abstract Recent advances in AI have catalyzed the adoption of intelligent educational tools, yet many semantic retrieval systems remain ill-suited to the unique linguistic and structural characteristics of academic content. This study prese...

Attack-Aware Deepfake Detection Under Counter-Forensic Manipulations

The rapid proliferation of AI-generated and manipulated visual content requires forensic detectors that remain reliable after routine processing and deliberate counter-forensic modification. This paper presents an attack-aware deepfake dete...

Calibration and Orientation of Cameras in Computer Vision

One of my greatest hates is the edited book with chapters from a number of different authors, some of which have evidently been written in haste against the final deadline, and most of which show marked divergence of content, opinion, notat...

Global Calibration of Multiple Cameras Based on Sphere Targets

Global calibration methods for multi-camera system are critical to the accuracy of vision measurement. Proposed in this paper is such a method based on several groups of sphere targets and a precision auxiliary camera. Each camera to be cal...

Video-Based Deep Learning Approach for 3D Human Movement Analysis in Institutional Hallways: A Smart Hallway

New artificial intelligence- (AI) based marker-less motion capture models provide a basis for quantitative movement analysis within healthcare and eldercare institutions, increasing clinician access to quantitative movement data and improvi...

Calibration and Orientation of Cameras in Computer Vision

Computer Vision and Pattern Recognition 2020

This special issue covers a wide range of topics from the area of Computer Vision, Pattern Recognition, and Machine Learning.This breadth of scope is reflected by the papers included in this special issue, which touch topics including geome...

Integrating Computer Vision: Advancements in Fire and Smoke Detection Using CNNs

Conventional fire detection systems, which depend on smoke and fire sensors, frequently have problems with calibration, susceptibility to environmental changes, and the requirement for ongoing maintenance. These flaws can result in unfavora...

Camera Calibration in High-Speed Robotic Assembly Operations

The increase in positioning accuracy and repeatability allowed the integration of robots in assembly operations using guidance systems (structured applications) or video acquisition systems (unstructured applications). This paper proposes a...

SFCN: Symmetric feature comparison network for detecting ischemic stroke lesions on CT images

Abstract Ischemic stroke is the most common stroke and the leading cause of disability and death in the world. Computed tomography (CT) is a popular and economical diagnostic device for the stroke, However the ischemic stroke lesions are no...

New topic horizons for drone systems and applications

Summary This journal (Drone Systems and Applications; DSA) conducted a targeted “horizon scan” during 2022 within our team of editors and associate editors. We asked—Which research areas currently under-represented in Drone Systems and Appl...

Emerging Topics in Computer Vision

The state-of-the art in computer vision: theory, applications, and programmingWhether you're a working engineer, developer, researcher, or student, this is your single authoritative source for today's key computer vision innovations. Gerard...

Handbook of computer vision and applications

Contents of Volume One: Preface. Contributors. B. Jahne, Introduction. Illumination and Image Formation. H. Hausecker, Radiation. H. Hausecker, Interaction of Radiation with Matter. P. Geisler, Geometric and Wave Optics. H. Hausecker, Radio...

Computer Vision

This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the worl...

On Calibration of Modern Neural Networks

Confidence calibration -- the problem of predicting probability estimates representative of the true correctness likelihood -- is important for classification models in many applications. We discover that modern neural networks, unlike thos...

A Simple Baseline for Bayesian Uncertainty in Deep Learning

We propose SWA-Gaussian (SWAG), a simple, scalable, and general purpose approach for uncertainty representation and calibration in deep learning. Stochastic Weight Averaging (SWA), which computes the first moment of stochastic gradient desc...