New method for sensing non-planar surfaces using ERT.
problem Limited computational techniques for planar surfaces in ERT-based sensing skins.
method Generalized ERT to non-planar surfaces using Riemannian geometry.
result Feasibility and applicability of ERT-based sensing skins for non-planar geometries demonstrated.
A new platform helps detect and manage pressure ulcers.
problem Detecting and managing pressure ulcers efficiently.
method Convolutional neural networks and transfer learning.
result Automated skin damage and pressure ulcer assessment tool.
Continuum mechanics theory describes skin's complex anisotropic behavior.
problem Modeling the anisotropic tearing of skin.
method Finsler geometry fiber bundle approach, variational method, phase-field mechanics.
result Analytical solutions capture experimental data on skin tearing.
Standard economic theory makes an allowance for the agency problem, but not the compounding of moral hazard in the presence of informational opacity, particularly in what concerns high-impact events in fat tailed domains (under slow convergence for the law of large numbers). Nor did it look at exposure as a filter that…
The paper investigates skin tone estimation and its impact on dermatology model performance.
problem The impact of skin tone on dermatology model performance is not well understood.
method The authors use individual typology angle (ITA) to estimate skin tone in dermatology datasets and analyze model performance.
result There is no measurable correlation between model performance and ITA values.
A reliable human skin detection method that is adaptable to different human skin colours and illu- mination conditions is essential for better human skin segmentation. Even though different human skin colour detection solutions have been successfully applied, they are prone to false skin detection and are not able to c…
Formula found for skinning map contraction in hyperbolic geometry.
problem Finding the contraction constant of skinning maps.
method Elementary hyperbolic geometry and moduli spaces of hyperbolic manifolds.
result Explicit formula for contraction constant.
Paper presents an active learning method to reduce skin lesion analysis annotation cost.
problem High cost of manual annotation in skin lesion analysis.
method Decoupled sample selection criteria for informativeness and representativeness, combined with pixel space aggregation for data augmentation.
result 50% annotated data suffices for state-of-the-art performance, outperforming other methods.
Certain classes of 3-manifolds, following Thurston, give rise to a 'skinning map', a self-map of the Teichmüller space of the boundary. This paper examines the skinning map of a 3-manifold M, a genus-2 handlebody with two rank-1 cusps. We exploit an orientation-reversing isometry of M to conclude that the skinning map …
Let M be a hyperbolic 3-manifold with nonempty totally geodesic boundary. We prove that there are upper and lower bounds on the diameter of the skinning map of M that depend only on the volume of the hyperbolic structure with totally geodesic boundary, answering a question of Y. Minsky. This is proven via a filling the…
U-Net network trained for skin lesion segmentation in ISIC challenge.
problem Skin lesion segmentation in medical imaging.
method Trained a U-Net network with adjusted loss function and post-processing.
result Improved accuracy in segmenting skin lesions.
Deep learning improves skin cancer detection.
problem Early detection of skin cancer is challenging due to lack of professionals and instruments.
method Overview of recent deep learning models applied to skin cancer detection.
result Deep learning models enhance skin cancer detection accuracy.
System detects and classifies skin cancer using CNN.
problem Early detection and classification of skin cancer is challenging and costly.
method Used MNIST HAM-10000 dataset, image processing, deep learning (CNN), and transfer learning (ResNet).
result CNN model achieved 0.88 precision, 0.74 recall, and 0.77 f1-score.
New method detects structural damage quickly without knowing post-damage feature distribution.
problem Quickly identify structural damage with unknown post-damage feature distribution.
method Sequential change-point detection using maximum likelihood estimation.
result Accurately identifies structural damage in various tests.
New dataset and approach improve skin cancer detection accuracy.
problem Lack of patient clinical information in automated skin cancer detection.
method Introduced a new dataset with clinical images and patient information. Combined clinical data with dermoscopy images using deep learning models.
result Combining clinical data improves skin cancer detection accuracy by around 7%.
Paper finds gender classification accuracy varies by skin type, not ethnicity.
problem Unequal performance of face classification services across skin types and genders.
method Stability experiments, image manipulation, and post-hoc explanation techniques.
result Lip, eye, and cheek structure differences, not skin type, cause gender classification discrepancies.
Robots adapt to damage with a single policy and diagnosis.
problem Robotic failure due to damage during mission-critical tasks.
method Damage-aware control architecture using supervised learning for diagnosis and policy adaptation.
result Single-shot diagnosis and adaptation achieved with a single policy.
Study finds object detection systems have higher error rates for darker-skinned pedestrians.
problem Predictive bias in object detection systems for pedestrians with different skin tones.
method Annotated a large dataset and compared performance between skin tone groups, investigating factors like time of day and occlusion.
result Predictive bias in object detection systems is not solely due to more difficult scenes for darker-skinned pedestrians.
Study reveals AI skin cancer classifiers underperform for darker skin phototypes, advocating for fairness auditing.
problem AI bias in dermatology, particularly for darker skin phototypes.
method Predictive Representativity (PR) framework, evaluating classifiers on HAM10000 and BOSQUE Test sets.
result Substantial performance disparities by skin phototype, highlighting AI bias.
MobileNet CNN achieves high accuracy in skin disease classification on Android.
problem Skin disease classification using smartphone technology.
method Transfer learning on MobileNet, imbalanced dataset handling (sampling and preprocessing), and data augmentation.
result Oversampling and data augmentation on preprocessing input data achieved 94.4% accuracy.
This paper proposes an innovative method for segmentation of skin lesions in dermoscopy images developed by the authors, based on fuzzy classification of pixels and histogram thresholding.
This is the first in a series of papers where we develop new structural elements on singular area minimizing hypersurfaces, the skin structures. They disclose previously unapproachable and largely unexpected geometric and analytic properties of such hypersurfaces.
MedAusbild team won ISIC challenge by classifying seven skin diseases.
problem Skin disease classification using medical images.
method Employed deep learning, specifically convolutional neural networks (CNNs), for seven skin disease classification.
result MedAusbild team won ISIC challenge 2018.
Deep learning models outperform dermatologists in skin cancer classification.
problem Skin cancer classification using dermoscopy images.
method Different pre-trained deep learning architectures (DenseNet 201, ResNet 152, Inception v3, InceptionResNet v2) applied on dermoscopy images.
result DenseNet 201 achieved highest AUC values for melanoma and basal cell carcinoma.
We prove that a Bers slice is never algebraic, meaning that its Zariski closure in the character variety has strictly larger dimension. A corollary is that skinning maps are never constant. The proof uses grafting and the theory of complex projective structures.
CNN automates vitiligo lesion segmentation quickly and accurately.
problem Manual segmentation of vitiligo lesions is time-consuming and inconsistent.
method U-Net architecture with modified contracting path, followed by watershed algorithm refinement.
result CNN achieves 73.6% Jaccard Index, significantly outperforming state-of-the-art methods.
We show that the diameter of the skinning map of an acylindrical hyperbolic 3-manifold M is bounded on thick Teichmueller geodesic rays by a constant depending only on the thickness of the ray and the topological type of the boundary of M.
This paper reviews traditional and modern methods for detecting structural damage using vibrations.
problem Early warning of structural damage to maintain civil structures.
method Vibration-based methods and ML/DL algorithms.
result ML and DL algorithms show superior performance in detecting structural damage.
Proposes a multi-objective variational autoencoder for smart infrastructure damage detection.
problem Detecting and diagnosing damage in smart infrastructure using multi-way data.
method Multi-objective variational autoencoder (MVA) method for smart infrastructure damage detection and diagnosis.
result The method accurately detects structural damage, estimates severity, and captures damage locations.
Efficient skin lesion analysis combines deep CNN and handcrafted features.
problem Skin lesion analysis for melanoma detection.
method Combines deep learning and handcrafted features, introduces hybrid features.
result 0.841 score on validation dataset using SVM classifier.
Gaussian Process Regression improves damage assessment in structural health monitoring.
problem Inaccurate damage quantification in varying conditions and environments.
method Gaussian Process Regression models with Damage Indices for probabilistic damage assessment.
result The method provides probability-based decision-making for structural health monitoring.
We show that if the totally geodesic boundary of a compact hyperbolic 3-manifold M has a large collar of depth d, then the diameter of the skinning map of M is no more than A exp(-d) for some A depending only on the genus and injectivity radius of the boundary of M.
Uniform diameter bound for reflection group disk patterns.
problem Uniform bounded diameter conjecture for reflection groups.
method Skinning map analysis and discrete extremal width on Coxeter graph.
result Diameter of skinning image is bounded by a constant.
Improved skin lesion classification with neural networks and data augmentation.
problem Skin lesion classification accuracy improvement.
method Multi-scale convolutional neural networks and domain-specific image augmentation.
result Proposed method outperforms state-of-the-art approaches on ISIC2016 and ISIC2017 tasks.
Paper improves disaster damage detection using modern transfer learning.
problem Harder to obtain damaged examples than undamaged ones.
method Revisits classical bagging with modern transfer learning.
result Significantly outperforms existing methodologies.
Optimizes package types for e-commerce to reduce damage and costs.
problem Sub-optimal package types lead to damaged shipments and high costs.
method Multi-stage approach that balances shipment and damage costs using a scalable algorithm.
result Significant cost savings of tens of millions of dollars achieved.
We give a generalization of Thurston's Bounded Image Theorem for skinning maps, which applies to pared 3-manifolds with incompressible boundary that are not necessarily acylindrical. Along the way we study properties of divergent sequences in the deformation space of such a manifold, establishing the existence of compa…
Machine learning detects building damage in satellite images.
problem Extracting damage information from satellite imagery is slow and labor-intensive.
method Used four convolutional neural network models to detect damaged buildings.
result Models performed well in detecting damaged buildings in the 2010 Haiti earthquake.
Deep learning and entropy methods detect skin cancer outliers.
problem Detecting an outlier class in a skin cancer dataset.
method Ensemble of 13 CNNs, two outlier handling approaches, and meta-data integration.
result Successfully addressed the outlier class and improved diagnostic accuracy.
This is the third in a series of papers on the geometry and analysis of singular area minimizing hypersurfaces. We show how to derive obstruction and structure theories for scalar curvature constraints without imposing dimensional or topological restrictions on the underlying manifold. To this end, we use skin structur…
Generative Adversarial Networks create synthetic data for structural damage detection.
problem Data scarcity in structural damage detection.
method 1-D Wasserstein Deep Convolutional Generative Adversarial Networks (1-D WDCGAN-GP) for synthetic data generation.
result Generated synthetic data improves damage detection accuracy in 1-D Deep Convolutional Neural Networks.
Tornadoes are the most violent of all atmospheric storms. In a typical year, the United States experiences hundreds of tornadoes with associated damages on the order of one billion dollars. Community preparation and resilience would benefit from accurate predictions of these economic losses, particularly as populations…
A model predicts building damage locations in near real-time using intensity-based features.
problem Accurate and timely damage diagnosis of building structures after extreme events.
method Support vector machines and Bayesian optimization for probabilistic hazard intensity determination.
result The model achieves 83.1% accuracy in identifying damage locations in a reinforced concrete moment frame.
Generative model predicts remaining life of damaged structures.
problem Prognosis of damage and remaining useful life of structures.
method Generative adversarial networks (GANs) in a population-based SHM framework.
result Algorithm provides confident predictions about structures' remaining useful life.
Research shows higher damages may encourage more disclosure in corporate disputes.
problem How to resolve disputes over undisclosed material events in a way that encourages voluntary disclosure.
method Dynamic continuous-time model of management's equilibrium disclosure decision.
result Increased damages may lead to an endogenous increase in voluntary disclosure.
The paper studies circle packings using renormalization and subdivision rules.
problem Characterizing and proving properties of circle packings with specific subdivision rules.
method Iterations of skinning maps on Teichmüller spaces, renormalization theory, subdivision rules.
result Uniformly contracting renormalization operator and geometric inflexibility of circle packings.
Study uses machine learning to optimize antibiotic therapy for MRSA skin infections.
problem Optimizing antibiotic choice for MRSA skin infections due to reduced treatment options and side effects.
method Propensity score matching, machine learning models (SVM, RF, LASSO), counterfactual analysis.
result RF model shows stronger treatment heterogeneity and potential for therapy change.
Deep learning skin lesion classifier explained using CAVs.
problem Limited acceptance of deep learning CAD systems due to opaque decision-making.
method Mapped human understandable concepts to RECOD model using CAVs.
result Classifier learns and encodes disease-related concepts in its latent representation.