AIMC Topic: Neural Networks, Computer

Clear Filters Showing 16801 to 16810 of 31376 articles

Practical fine-grained learning based anomaly classification for ECG image.

Artificial intelligence in medicine
As a widely used vital sign within cardiology, Electrocardiography (ECG) provides the basis for assessing heart function and diagnosing cardiovascular diseases. Automated anomaly detection for ECG plays an important role in improving patient diagnosi...

Development of convolutional neural networks for recognition of tenogenic differentiation based on cellular morphology.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The use of automated systems for image recognition is highly preferred for regenerative medicine applications to evaluate stem cell differentiation early in the culturing state with non-invasive methodologies instead of inva...

xECGNet: Fine-tuning attention map within convolutional neural network to improve detection and explainability of concurrent cardiac arrhythmias.

Computer methods and programs in biomedicine
Background and objectiveDetecting abnormal patterns within an electrocardiogram (ECG) is crucial for diagnosing cardiovascular diseases. We start from two unresolved problems in applying deep-learning-based ECG classification models to clinical pract...

Hierarchical CNN-based occlusal surface morphology analysis for classifying posterior tooth type using augmented images from 3D dental surface models.

Computer methods and programs in biomedicine
OBJECTIVE: 3D Digitization of dental model is growing in popularity for dental application. Classification of tooth type from single 3D point cloud model without assist of relative position among teeth is still a challenging task.

A Multitask Approach to Learn Molecular Properties.

Journal of chemical information and modeling
The endeavors to pursue a robust multitask model to resolve intertask correlations have lasted for many years. A multitask deep neural network, as the most widely used multitask framework, however, experiences several issues such as inconsistent perf...

A Deep Dive of Autoencoder Models on Low-Contrast Aquatic Images.

Sensors (Basel, Switzerland)
Public aquariums and similar institutions often use video as a method to monitor the behavior, health, and status of aquatic organisms in their environments. These video footages take up a sizeable amount of space and require the use of autoencoders ...

Pupil Size Prediction Techniques Based on Convolution Neural Network.

Sensors (Basel, Switzerland)
The size of one's pupil can indicate one's physical condition and mental state. When we search related papers about AI and the pupil, most studies focused on eye-tracking. This paper proposes an algorithm that can calculate pupil size based on a conv...

Audio-Based Drone Detection and Identification Using Deep Learning Techniques with Dataset Enhancement through Generative Adversarial Networks.

Sensors (Basel, Switzerland)
Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. In addition to their useful applications, an alarming concern in regard to the physic...

Integrating ensemble systems biology feature selection and bimodal deep neural network for breast cancer prognosis prediction.

Scientific reports
Breast cancer is a heterogeneous disease. To guide proper treatment decisions for each patient, robust prognostic biomarkers, which allow reliable prognosis prediction, are necessary. Gene feature selection based on microarray data is an approach to ...

Improve automatic detection of animal call sequences with temporal context.

Journal of the Royal Society, Interface
Many animals rely on long-form communication, in the form of songs, for vital functions such as mate attraction and territorial defence. We explored the prospect of improving automatic recognition performance by using the temporal context inherent in...