Artificial Intelligence Medical Compendium

Collecting a large amount of measured configuration data for robots entails high costs and time, which restricts the widespread use of neural networks for robot error prediction and compensation. In this study, a "transfer network" is established by ... read more 

In medical image segmentation, convolutional neural networks (CNNs) and transformers are dominant. For CNNs, given the local receptive fields of convolutional layers, long-range spatial correlations are captured through consecutive convolutions and p... read more 

Emerging virtual reality (VR) applications bring significant challenges to spherical image compression. Spherical images are first converted into planar images using projections like the equirectangular projection (ERP) to facilitate compression. Met... read more 

Stereopsis has widespread appeal in computer vision and robotics as it is the predominant way by which we perceive depth to navigate our 3D world. Event cameras are novel bio-inspired sensors that detect per-pixel brightness changes asynchronously, w... read more 

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The rapid advancement of generative artificial intelligence (AI) has enabled machines to produce creative outputs, such as artworks, that rival human creations. However, despite these technological achievements, public acceptance and valuation of AI-... read more 

This study presents FCRNet, a Fast Fourier Convolution Residual Network, tailored for fault diagnosis of mine ventilation bearings under complex operating conditions. By integrating residual learning with Fast Fourier Convolution (FFC), FCRNet employ... read more 

Strategies to predict neonatal seizure risk have typically focused on long-term static predictions with prediction horizons spanning days during the acute postnatal period. Higher temporal resolution or short-horizon neonatal seizure prediction, on t... read more 

Museum architecture is essential for preserving cultural heritage. Understanding the spatio-temporal evolution of visitor preferences, image perceptions, and driving factors is vital for promoting cultural development. However, traditional methods su... read more 

This paper presents a novel privacy-preserving architecture, a fusion of Federated Learning with Personalized Models and Differential Privacy (FLPMDP), for diagnosing arrhythmia from 12-lead electrocardiogram (ECG) signals. The architecture supports ... read more