Artificial intelligence for safety-critical systems in industrial and transportation domains: A survey
Artificial Intelligence (AI) can enable the development of next-generation autonomous safety-
critical systems in which Machine Learning (ML) algorithms learn optimized and safe …
critical systems in which Machine Learning (ML) algorithms learn optimized and safe …
Medsegdiff: Medical image segmentation with diffusion probabilistic model
Abstract Diffusion Probabilistic Model (DPM) has recently become one of the hottest topics in
computer vision. Its image generation applications, such as Imagen, Latent Diffusion …
computer vision. Its image generation applications, such as Imagen, Latent Diffusion …
Potential applications of connected vehicles in pavement condition evaluation: a brief review
M Samie, A Golroo, D Tavakoli… - Road Materials and …, 2024 - Taylor & Francis
Road authorities are concerned with maintaining the road condition at a high level of service
to minimise user and agency costs. For this purpose, they have to monitor the road condition …
to minimise user and agency costs. For this purpose, they have to monitor the road condition …
Polymax: General dense prediction with mask transformer
Dense prediction tasks, such as semantic segmentation, depth estimation, and surface
normal prediction, can be easily formulated as per-pixel classification (discrete outputs) or …
normal prediction, can be easily formulated as per-pixel classification (discrete outputs) or …
Suppress and Rebalance: Towards Generalized Multi-Modal Face Anti-Spoofing
Abstract Face Anti-Spoofing (FAS) is crucial for securing face recognition systems against
presentation attacks. With advancements in sensor manufacture and multi-modal learning …
presentation attacks. With advancements in sensor manufacture and multi-modal learning …
Anatomically-aware uncertainty for semi-supervised image segmentation
Semi-supervised learning relaxes the need of large pixel-wise labeled datasets for image
segmentation by leveraging unlabeled data. A prominent way to exploit unlabeled data is to …
segmentation by leveraging unlabeled data. A prominent way to exploit unlabeled data is to …
Scoring Bayesian Neural Networks for learning from inconsistent labels in surface defect segmentation
This paper focus on surface defect segmentation uncertainty challenges that arise due to
human errors and biases in the data annotation process, particularly in ambiguous transition …
human errors and biases in the data annotation process, particularly in ambiguous transition …
Tyche: Stochastic In-Context Learning for Medical Image Segmentation
Existing learning-based solutions to medical image segmentation have two important
shortcomings. First for most new segmentation tasks a new model has to be trained or fine …
shortcomings. First for most new segmentation tasks a new model has to be trained or fine …
[HTML][HTML] Network response of brain microvasculature to neuronal stimulation
Neurovascular coupling (NVC), or the adjustment of blood flow in response to local
increases in neuronal activity is a hallmark of healthy brain function, and the physiological …
increases in neuronal activity is a hallmark of healthy brain function, and the physiological …
Long-term prediction of daily solar irradiance using Bayesian deep learning and climate simulation data
Solar Irradiance depicts the light energy produced by the Sun that hits the Earth. This energy
is important for renewable energy generation and is intrinsically fluctuating. Forecasting …
is important for renewable energy generation and is intrinsically fluctuating. Forecasting …