AIMC Topic: Neural Networks, Computer

Clear Filters Showing 14511 to 14520 of 31376 articles

Hyperspectral Image Labeling and Classification Using an Ensemble Semi-Supervised Machine Learning Approach.

Sensors (Basel, Switzerland)
Hyperspectral remote sensing has tremendous potential for monitoring land cover and water bodies from the rich spatial and spectral information contained in the images. It is a time and resource consuming task to obtain groundtruth data for these ima...

GAN-Based Image Colorization for Self-Supervised Visual Feature Learning.

Sensors (Basel, Switzerland)
Large-scale labeled datasets are generally necessary for successfully training a deep neural network in the computer vision domain. In order to avoid the costly and tedious work of manually annotating image datasets, self-supervised learning methods ...

Convolutional Blur Attention Network for Cell Nuclei Segmentation.

Sensors (Basel, Switzerland)
Accurately segmented nuclei are important, not only for cancer classification, but also for predicting treatment effectiveness and other biomedical applications. However, the diversity of cell types, various external factors, and illumination conditi...

SiamMixer: A Lightweight and Hardware-Friendly Visual Object-Tracking Network.

Sensors (Basel, Switzerland)
Siamese networks have been extensively studied in recent years. Most of the previous research focuses on improving accuracy, while merely a few recognize the necessity of reducing parameter redundancy and computation load. Even less work has been don...

PyUUL provides an interface between biological structures and deep learning algorithms.

Nature communications
Structural bioinformatics suffers from the lack of interfaces connecting biological structures and machine learning methods, making the application of modern neural network architectures impractical. This negatively affects the development of structu...

Application of Deep Learning Technology in Glioma.

Journal of healthcare engineering
A common and most basic brain tumor is glioma that is exceptionally dangerous to health of various patients. A glioma segmentation, which is primarily magnetic resonance imaging (MRI) oriented, is considered as one of common tools developed for docto...

Pattern Recognition of Holographic Image Library Based on Deep Learning.

Journal of healthcare engineering
The final loss function in the deep learning neural network is composed of other functions in the network. Due to the existence of a large number of non-linear functions such as activation functions in the network, the entire deep learning model pres...

An EEG Classification-Based Method for Single-Trial N170 Latency Detection and Estimation.

Computational and mathematical methods in medicine
Event-related potentials (ERPs) can reflect the high-level thinking activities of the brain. In ERP analysis, the superposition and averaging method is often used to estimate ERPs. However, the single-trial ERP estimation can provide researchers with...

Protocol for the diagnosis of keratoconus using convolutional neural networks.

PloS one
Keratoconus is the corneal disease with the highest reported incidence of 1:2000. The treatment's level of success highly depends on how early it was started. Subsequently, a fast and highly capable diagnostic tool is crucial. While there are many co...

Deploying Machine Learning Models Using Progressive Web Applications: Implementation Using a Neural Network Prediction Model for Pneumonia Related Child Mortality in The Gambia.

Frontiers in public health
BACKGROUND: Translating research outputs into practical tools for medical practitioners is a neglected area and could have a substantial impact. One of the barriers to implementing artificial intelligence (AI) and machine learning (ML) applications i...