AIMC Topic: Algorithms

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GZSL-Lite: A Lightweight Generalized Zero-Shot Learning Network for SSVEP-Based BCIs.

IEEE transactions on bio-medical engineering
Generalized zero-shot learning (GZSL) networks offer promising avenues for the development of user-friendly steady-state visual evoked potential (SSVEP) based brain-computer interfaces (BCIs), aiming to alleviate the training burden on users. These n...

Evaluation of a Low-Cost Amplifier With System Optimization in Thermoacoustic Tomography: Characterization and Imaging of Ex-Vivo and In-Vivo Samples.

IEEE transactions on bio-medical engineering
Microwave-induced thermoacoustic tomography (TAT) is a hybrid imaging technique that combines microwave excitation with ultrasound detection to create detailed images of biological tissue. Most TAT systems require a costly amplification system (or a ...

A Novel NICU Sleep State Stratification: Multiperspective Features, Adaptive Feature Selection and Ensemble Model.

IEEE transactions on bio-medical engineering
The examination of sleep patterns in newborns, particularly premature infants, is crucial for understanding neonatal development. This study presents an automated multi-sleep state classification approach for infants in neonatal intensive care units ...

Deep Learning-Based Saturation Compensation for High Dynamic Range Multispectral Fluorescence Lifetime Imaging.

IEEE transactions on bio-medical engineering
In multispectral fluorescence lifetime imaging (FLIm), achieving consistent imaging quality across all spectral channels is crucial for accurately identifying a wide range of fluorophores. However, these essential measurements are frequently compromi...

Deciphering Explicit and Implicit Features for Reliable, Interpretable, and Actionable User Churn Prediction in Online Video Games.

IEEE transactions on visualization and computer graphics
The burgeoning online video game industry has sparked intense competition among providers to both expand their user base and retain existing players, particularly within social interaction genres. To anticipate player churn, there is an increasing re...

Efficient Integration of Neural Representations for Dynamic Humans.

IEEE transactions on visualization and computer graphics
While numerous studies have explored NeRF-based novel view synthesis for dynamic humans, they often require training that exceeds several hours, limiting their practicality. Efforts to improve training efficiency have also encountered challenges beca...

KMTLabeler: An Interactive Knowledge-Assisted Labeling Tool for Medical Text Classification.

IEEE transactions on visualization and computer graphics
The process of labeling medical text plays a crucial role in medical research. Nonetheless, creating accurately labeled medical texts of high quality is often a time-consuming task that requires specialized domain knowledge. Traditional methods for g...

Sketch2Human: Deep Human Generation With Disentangled Geometry and Appearance Constraints.

IEEE transactions on visualization and computer graphics
Geometry- and appearance-controlled full-body human image generation is an interesting but challenging task. Existing solutions are either unconditional or dependent on coarse conditions (e.g., pose, text), thus lacking explicit geometry and appearan...

Machine learning in biosignal analysis from wearable devices.

Materials horizons
The advancement of wearable bioelectronics has significantly improved real-time biosignal monitoring, enabling continuous health tracking and providing personalized medical insights. However, the sheer volume and complexity of biosignal data collecte...

[Robotic autonomous surgery in gastrointestinal practice: a viable pathway or an aspirational vision in the artificial intelligence era?].

Zhonghua wei chang wai ke za zhi = Chinese journal of gastrointestinal surgery
The deep integration of artificial intelligence (AI) and multimodal data in the medical field presents vast application prospects, with its implementation in robotic surgery still in the early stages. Surgical robots assist surgeons in decision-makin...