AIMC Topic: Neural Networks, Computer

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Basis operator network: A neural network-based model for learning nonlinear operators via neural basis.

Neural networks : the official journal of the International Neural Network Society
It is widely acknowledged that neural networks can approximate any continuous (even measurable) functions between finite-dimensional Euclidean spaces to arbitrary accuracy. Recently, the use of neural networks has started emerging in infinite-dimensi...

Self-supervision assisted multimodal remote sensing image classification with coupled self-looping convolution networks.

Neural networks : the official journal of the International Neural Network Society
Recently, remote sensing community has seen a surge in the use of multimodal data for different tasks such as land cover classification, change detection and many more. However, handling multimodal data requires synergistically using the information ...

Automatic sex estimation using deep convolutional neural network based on orthopantomogram images.

Forensic science international
Sex estimation is very important in forensic applications as part of individual identification. Morphological sex estimation methods predominantly focus on anatomical measurements. Based on the close relationship between sex chromosome genes and faci...

Need for objective task-based evaluation of deep learning-based denoising methods: A study in the context of myocardial perfusion SPECT.

Medical physics
BACKGROUND: Artificial intelligence-based methods have generated substantial interest in nuclear medicine. An area of significant interest has been the use of deep-learning (DL)-based approaches for denoising images acquired with lower doses, shorter...

Deep learning methods for medical image fusion: A review.

Computers in biology and medicine
The image fusion methods based on deep learning has become a research hotspot in the field of computer vision in recent years. This paper reviews these methods from five aspects: Firstly, the principle and advantages of image fusion methods based on ...

Automated inter-patient arrhythmia classification with dual attention neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Arrhythmia classification based on electrocardiograms (ECG) can enhance clinical diagnostic efficiency. However, due to the significant differences in the number of different categories of heartbeats, the performance of cla...

BCU-Net: Bridging ConvNeXt and U-Net for medical image segmentation.

Computers in biology and medicine
Medical image segmentation enables doctors to observe lesion regions better and make accurate diagnostic decisions. Single-branch models such as U-Net have achieved great progress in this field. However, the complementary local and global pathologica...

Person-Specific Gaze Estimation from Low-Quality Webcam Images.

Sensors (Basel, Switzerland)
Gaze estimation is an established research problem in computer vision. It has various applications in real life, from human-computer interactions to health care and virtual reality, making it more viable for the research community. Due to the signifi...

Automated classification of polyps using deep learning architectures and few-shot learning.

BMC medical imaging
BACKGROUND: Colorectal cancer is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is a colonoscopy. However, not all colon polyps have the risk of becoming cancerous. Therefore, polyps are classified using different ...

Validation of genetic variants from NGS data using deep convolutional neural networks.

BMC bioinformatics
Accurate somatic variant calling from next-generation sequencing data is one most important tasks in personalised cancer therapy. The sophistication of the available technologies is ever-increasing, yet, manual candidate refinement is still a necessa...