AIMC Topic: Neural Networks, Computer

Clear Filters Showing 12561 to 12570 of 31376 articles

Prediction of Retail Price of Sporting Goods Based on LSTM Network.

Computational intelligence and neuroscience
Commodity prices play a unique role as a lever to regulate the economy. Price forecasting is an important part of macrodecision-making and micromanagement. Because there are many factors affecting the price of goods, price prediction has become a dif...

Human Sports Action and Ideological and PoliticalEvaluation by Lightweight Deep Learning Model.

Computational intelligence and neuroscience
The purpose is to automatically and quickly analyze whether the rope skipping actions conform to the standards and give correct guidance and training plans. Firstly, aiming at the problem of motion analysis, a deep learning (DL) framework is proposed...

Towards automated coronary artery segmentation: A systematic review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Vessel segmentation is the first processing stage of 3D medical images for both clinical and research use. Current segmentation methods are tedious and time consuming, requiring significant manual correction and hence are in...

Breaking CAPTCHA with Capsule Networks.

Neural networks : the official journal of the International Neural Network Society
Convolutional Neural Networks have achieved state-of-the-art performance in image classification. Their lack of ability to recognise the spatial relationship between features, however, leads to misclassification of the variants of the same image. Cap...

Application of deep learning methods: From molecular modelling to patient classification.

Experimental cell research
We are now well into the information driven age with complex, heterogeneous, datasets in the biological sciences continuing to grow at a rapid pace. Moreover, distilling of such datasets, to find new governing principles, are underway. Leading the su...

EEG based depression recognition using improved graph convolutional neural network.

Computers in biology and medicine
Depression is a global psychological disease that does serious harm to people. Traditional diagnostic method of the doctor-patient communication, is not objective and accurate enough. Thus, a more accurate and objective method for depression detectio...

NILINKER: Attention-based approach to NIL Entity Linking.

Journal of biomedical informatics
The existence of unlinkable (NIL) entities is a major hurdle affecting the performance of Named Entity Linking approaches, and, consequently, the performance of downstream models that depend on them. Existing approaches to deal with NIL entities focu...

SM-SegNet: A Lightweight Squeeze M-SegNet for Tissue Segmentation in Brain MRI Scans.

Sensors (Basel, Switzerland)
In this paper, we propose a novel squeeze M-SegNet (SM-SegNet) architecture featuring a fire module to perform accurate as well as fast segmentation of the brain on magnetic resonance imaging (MRI) scans. The proposed model utilizes uniform input pat...

DRSNFuse: Deep Residual Shrinkage Network for Infrared and Visible Image Fusion.

Sensors (Basel, Switzerland)
Infrared images are robust against illumination variation and disguises, containing the sharp edge contours of objects. Visible images are enriched with texture details. Infrared and visible image fusion seeks to obtain high-quality images, keeping t...

Image Classification Method Based on Multi-Agent Reinforcement Learning for Defects Detection for Casting.

Sensors (Basel, Switzerland)
A casting image classification method based on multi-agent reinforcement learning is proposed in this paper to solve the problem of casting defects detection. To reduce the detection time, each agent observes only a small part of the image and can mo...