AIMC Topic: Neural Networks, Computer

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Automatic identification of triple negative breast cancer in ultrasonography using a deep convolutional neural network.

Scientific reports
Triple negative (TN) breast cancer is a subtype of breast cancer which is difficult for early detection and the prognosis is poor. In this paper, 910 benign and 934 malignant (110 TN and 824 NTN) B-mode breast ultrasound images were collected. A Resn...

EEGdenoiseNet: a benchmark dataset for deep learning solutions of EEG denoising.

Journal of neural engineering
Deep learning (DL) networks are increasingly attracting attention across various fields, including electroencephalography (EEG) signal processing. These models provide comparable performance to that of traditional techniques. At present, however, the...

Research on Volleyball Video Intelligent Description Technology Combining the Long-Term and Short-Term Memory Network and Attention Mechanism.

Computational intelligence and neuroscience
With the development of computer technology, video description, which combines the key technologies in the field of natural language processing and computer vision, has attracted more and more researchers' attention. Among them, how to objectively an...

Chinese Language Feature Analysis Based on Multilayer Self-Organizing Neural Network and Data Mining Techniques.

Computational intelligence and neuroscience
As one of the oldest languages in the world, Chinese has a long cultural history and unique language charm. The multilayer self-organizing neural network and data mining techniques have been widely used and can achieve high-precision prediction in di...

Deep learning for automated detection and numbering of permanent teeth on panoramic images.

Dento maxillo facial radiology
OBJECTIVE: This study aimed to evaluate an automated detection system to detect and classify permanent teeth on orthopantomogram (OPG) images using convolutional neural networks (CNNs).

Self-supervised driven consistency training for annotation efficient histopathology image analysis.

Medical image analysis
Training a neural network with a large labeled dataset is still a dominant paradigm in computational histopathology. However, obtaining such exhaustive manual annotations is often expensive, laborious, and prone to inter and intra-observer variabilit...

Using a multi-head, convolutional neural network with data augmentation to improve electropherogram classification performance.

Forensic science international. Genetics
DNA profiles are generated in forensic biology laboratories around the world. It is possible that these profiles are assessed by two independent people in order for the profiles to be 'read'. Recent work has been carried out to develop a neural netwo...

VPNET: Variable Projection Networks.

International journal of neural systems
In this paper, we introduce VPNet, a novel model-driven neural network architecture based on variable projection (VP). Applying VP operators to neural networks results in learnable features, interpretable parameters, and compact network structures. T...

Automated detection of leukemia by pretrained deep neural networks and transfer learning: A comparison.

Medical engineering & physics
Leukemia is usually diagnosed by viewing the smears of blood and bone marrow using microscopes and complex Cytochemical tests can be used to authorize and classify leukemia. But these methods are costly, slow and affected by the proficiency and exper...