AIMC Topic: Neural Networks, Computer

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Geometric Deep Learning Using Vascular Surface Meshes for Modality-Independent Unruptured Intracranial Aneurysm Detection.

IEEE transactions on medical imaging
Early detection of unruptured intracranial aneurysms (UIAs) enables better rupture risk and preventative treatment assessment. UIAs are usually diagnosed on Time-of-Flight Magnetic Resonance Angiographs (TOF-MRA) or contrast-enhanced Computed Tomogra...

Eye-Gaze-Guided Vision Transformer for Rectifying Shortcut Learning.

IEEE transactions on medical imaging
Learning harmful shortcuts such as spurious correlations and biases prevents deep neural networks from learning meaningful and useful representations, thus jeopardizing the generalizability and interpretability of the learned representation. The situ...

EPT-Net: Edge Perception Transformer for 3D Medical Image Segmentation.

IEEE transactions on medical imaging
The convolutional neural network has achieved remarkable results in most medical image seg- mentation applications. However, the intrinsic locality of convolution operation has limitations in modeling the long-range dependency. Although the Transform...

Robust Peak Detection for Holter ECGs by Self-Organized Operational Neural Networks.

IEEE transactions on neural networks and learning systems
Although numerous R-peak detectors have been proposed in the literature, their robustness and performance levels may significantly deteriorate in low-quality and noisy signals acquired from mobile electrocardiogram (ECG) sensors, such as Holter monit...

FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation.

IEEE transactions on neural networks and learning systems
The increase of available large clinical and experimental datasets has contributed to a substantial amount of important contributions in the area of biomedical image analysis. Image segmentation, which is crucial for any quantitative analysis, has es...

A White-Box Testing for Deep Neural Networks Based on Neuron Coverage.

IEEE transactions on neural networks and learning systems
With the introduction of neuron coverage as a testing criterion for deep neural networks (DNNs), covering more neurons to detect more internal logic of DNNs became the main goal of many research studies. While some works had made progress, some new c...

Prototype-Based Interpretation of the Functionality of Neurons in Winner-Take-All Neural Networks.

IEEE transactions on neural networks and learning systems
Prototype-based learning (PbL) using a winner-take-all (WTA) network based on minimum Euclidean distance (ED-WTA) is an intuitive approach to multiclass classification. By constructing meaningful class centers, PbL provides higher interpretability an...

Entity Summarization via Exploiting Description Complementarity and Salience.

IEEE transactions on neural networks and learning systems
Entity summarization is a novel and efficient way to understand real-world facts and solve the increasing information overload problem in large-scale knowledge graphs (KG). Existing studies mainly rely on ranking independent entity descriptions as a ...

A Perifacial EMG Acquisition System for Facial-Muscle-Movement Recognition.

Sensors (Basel, Switzerland)
This paper proposes a portable wireless transmission system for the multi-channel acquisition of surface electromyography (EMG) signals. Because EMG signals have great application value in psychotherapy and human-computer interaction, this system is ...

Effective Local and Secondary Protein Structure Prediction by Combining a Neural Network-Based Approach with Extensive Feature Design and Selection without Reliance on Evolutionary Information.

International journal of molecular sciences
Protein structure prediction continues to pose multiple challenges despite outstanding progress that is largely attributable to the use of novel machine learning techniques. One of the widely used representations of local 3D structure-protein blocks ...