AI Medical Compendium Journal:
International journal of neural systems

Showing 1 to 10 of 223 articles

Continual Learning by Contrastive Learning of Regularized Classes in Multivariate Gaussian Distributions.

International journal of neural systems
Deep neural networks struggle with incremental updates due to catastrophic forgetting, where newly acquired knowledge interferes with the learned previously. Continual learning (CL) methods aim to overcome this limitation by effectively updating the ...

Understanding the Spatio-Temporal Coupling of Spikes and Spindles in Focal Epilepsy Through a Network-Level Computational Model.

International journal of neural systems
The electrophysiological findings have shown that epileptiform spikes triggering sleep spindles within 1[Formula: see text]s across multiple channels are commonly observed during sleep in focal epilepsy (FE). Such spatio-temporal couplings of spikes ...

Minimal Neural Network Conditions for Encoding Future Interactions.

International journal of neural systems
Space and time are fundamental attributes of the external world. Deciphering the brain mechanisms involved in processing the surrounding environment is one of the main challenges in neuroscience. This is particularly defiant when situations change ra...

Frequency-Assisted Local Attention in Lower Layers of Visual Transformers.

International journal of neural systems
Since vision transformers excel at establishing global relationships between features, they play an important role in current vision tasks. However, the global attention mechanism restricts the capture of local features, making convolutional assistan...

End-User Confidence in Artificial Intelligence-Based Predictions Applied to Biomedical Data.

International journal of neural systems
Applications of Artificial Intelligence (AI) are revolutionizing biomedical research and healthcare by offering data-driven predictions that assist in diagnoses. Supervised learning systems are trained on large datasets to predict outcomes for new te...

Architecture Knowledge Distillation for Evolutionary Generative Adversarial Network.

International journal of neural systems
Generative Adversarial Networks (GANs) are effective for image generation, but their unstable training limits broader applications. Additionally, neural architecture search (NAS) for GANs with one-shot models often leads to insufficient subnet traini...

Self-Supervised Image Segmentation Using Meta-Learning and Multi-Backbone Feature Fusion.

International journal of neural systems
Few-shot segmentation (FSS) aims to reduce the need for manual annotation, which is both expensive and time-consuming. While FSS enhances model generalization to new concepts with only limited test samples, it still relies on a substantial amount of ...

Multi-Label Zero-Shot Learning Via Contrastive Label-Based Attention.

International journal of neural systems
Multi-label zero-shot learning (ML-ZSL) strives to recognize all objects in an image, regardless of whether they are present in the training data. Recent methods incorporate an attention mechanism to locate labels in the image and generate class-spec...

Unraveling the Differential Efficiency of Dorsal and Ventral Pathways in Visual Semantic Decoding.

International journal of neural systems
Visual semantic decoding aims to extract perceived semantic information from the visual responses of the human brain and convert it into interpretable semantic labels. Although significant progress has been made in semantic decoding across individual...

A Novel State Space Model with Dynamic Graphic Neural Network for EEG Event Detection.

International journal of neural systems
Electroencephalography (EEG) is a widely used physiological signal to obtain information of brain activity, and its automatic detection holds significant research importance, which saves doctors' time, improves detection efficiency and accuracy. Howe...