AIMC Topic: Algorithms

Clear Filters Showing 13071 to 13080 of 28713 articles

Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System.

Frontiers in public health
Blockchain is a recent revolutionary technology primarily associated with cryptocurrencies. It has many unique features including its acting as a decentralized, immutable, shared, and distributed ledger. Blockchain can store all types of data with be...

Automatic Rule Generation for Decision-Making in Context-Aware Systems Using Machine Learning.

Computational intelligence and neuroscience
With the increasing interest devoted to dynamic environments, a crucial aspect is revealed in context-aware systems to deal with the rapid changes occurring in users' surrounding environments at runtime. However, most context-aware systems with prede...

Data Analysis and Knowledge Mining of Machine Learning in Soil Corrosion Factors of the Pipeline Safety.

Computational intelligence and neuroscience
The purpose of this research is to enhance the ability of data analysis and knowledge mining in soil corrosion factors of the pipeline. According to its multifactor characteristics, the rough set algorithm is directly used to analyze and process the ...

Exploiting exercise electrocardiography to improve early diagnosis of atrial fibrillation with deep learning neural networks.

Computers in biology and medicine
Atrial fibrillation (AF) is the most common type of sustained arrhythmia. It results from abnormal irregularities in the electrical performance of the atria, and may cause heart thrombosis, stroke, arterial disease, thromboembolism, and heart failure...

Pulmonary emphysema quantification at low dose chest CT using Deep Learning image reconstruction.

European journal of radiology
PURPOSE: Quantitative analysis of emphysema volume is affected by the radiation dose and the CT reconstruction technique. We aim to evaluate the influence of a commercially available deep learning image reconstruction algorithm (DLIR) on the quantifi...

Knowledge Distillation and Student-Teacher Learning for Visual Intelligence: A Review and New Outlooks.

IEEE transactions on pattern analysis and machine intelligence
Deep neural models, in recent years, have been successful in almost every field, even solving the most complex problem statements. However, these models are huge in size with millions (and even billions) of parameters, demanding heavy computation pow...

Deep Learning for Person Re-Identification: A Survey and Outlook.

IEEE transactions on pattern analysis and machine intelligence
Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-overlapping cameras. With the advancement of deep neural networks and increasing demand of intelligent video surveillance, it has gained significantly increa...

Salient Object Detection in the Deep Learning Era: An In-Depth Survey.

IEEE transactions on pattern analysis and machine intelligence
As an essential problem in computer vision, salient object detection (SOD) has attracted an increasing amount of research attention over the years. Recent advances in SOD are predominantly led by deep learning-based solutions (named deep SOD). To ena...

Spatiotemporal Co-Attention Recurrent Neural Networks for Human-Skeleton Motion Prediction.

IEEE transactions on pattern analysis and machine intelligence
Human motion prediction aims to generate future motions based on the observed human motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling sequential data, recent works utilize RNNs to model human-skeleton motions on the obser...

Learning to Match Anchors for Visual Object Detection.

IEEE transactions on pattern analysis and machine intelligence
Modern CNN-based object detectors assign anchors for ground-truth objects under the restriction of object-anchor Intersection-over-Union (IoU). In this study, we propose a learning-to-match (LTM) method to break IoU restriction, allowing objects to m...