AIMC Topic: Algorithms

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Training a Feedforward Neural Network Using Hybrid Gravitational Search Algorithm with Dynamic Multiswarm Particle Swarm Optimization.

BioMed research international
One of the most well-known methods for solving real-world and complex optimization problems is the gravitational search algorithm (GSA). The gravitational search technique suffers from a sluggish convergence rate and weak local search capabilities wh...

Traffic Sign Detection Based on SSD Combined with Receptive Field Module and Path Aggregation Network.

Computational intelligence and neuroscience
The traditional traffic sign detection algorithm can not deal with the application scenarios such as intelligent transportation system or advanced assisted driving environment, and it is difficult to meet the application requirements in detection acc...

Optimal Deep Transfer Learning-Based Human-Centric Biomedical Diagnosis for Acute Lymphoblastic Leukemia Detection.

Computational intelligence and neuroscience
Human-centric biomedical diagnosis (HCBD) becomes a hot research topic in the healthcare sector, which assists physicians in the disease diagnosis and decision-making process. Leukemia is a pathology that affects younger people and adults, instigatin...

A meta-learning algorithm for respiratory flow prediction from FBG-based wearables in unrestrained conditions.

Artificial intelligence in medicine
The continuous monitoring of an individual's breathing can be an instrument for the assessment and enhancement of human wellness. Specific respiratory features are unique markers of the deterioration of a health condition, the onset of a disease, fat...

Long Jump Action Recognition Based on Deep Convolutional Neural Network.

Computational intelligence and neuroscience
Long jump is a test item of national student physical health monitoring, which can reflect the quality of students' lower limb strength. Long jump is a highly technical activity, which includes four basic movements: running aid, jumping, vacating, an...

Construction and Application of Talent Evaluation Model Based on Nonlinear Hierarchical Optimization Neural Network.

Computational intelligence and neuroscience
Talent assessment attracts the attention of researchers because of its important influence on business management issues. The traditional talent evaluation model has high sample selection cost and large calculation volume ratio, so it has become an u...

Robust adaptive fault detection and diagnosis observer design for a class of nonlinear systems with uncertainty and unknown time-varying internal delay.

ISA transactions
This paper introduces a novel robust adaptive fault detection and diagnosis (FDD) observer design approach for a class of nonlinear systems with parametric uncertainty, unknown system fault and time-varying internal delays. The conditions for the exi...

Can images crowdsourced from the internet be used to train generalizable joint dislocation deep learning algorithms?

Skeletal radiology
OBJECTIVE: Deep learning has the potential to automatically triage orthopedic emergencies, such as joint dislocations. However, due to the rarity of these injuries, collecting large numbers of images to train algorithms may be infeasible for many cen...

Adaptive 2-bits-triggered neural control for uncertain nonlinear multi-agent systems with full state constraints.

Neural networks : the official journal of the International Neural Network Society
This paper investigates an adaptive 2-bits-triggered neural control for a class of uncertain nonlinear multi-agent systems (MASs) with full state constraints. Considering the limitations of practical physical devices and operating conditions, MASs ma...

A review of ultrasonic sensing and machine learning methods to monitor industrial processes.

Ultrasonics
Supervised machine learning techniques are increasingly being combined with ultrasonic sensor measurements owing to their strong performance. These techniques also offer advantages over calibration procedures of more complex fitting, improved general...