AIMC Topic: Crowding

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Multi-Objective Particle Swarm Optimization Approach for Cost-Based Feature Selection in Classification.

IEEE/ACM transactions on computational biology and bioinformatics
Feature selection is an important data-preprocessing technique in classification problems such as bioinformatics and signal processing. Generally, there are some situations where a user is interested in not only maximizing the classification performa...

Online anomaly detection in crowd scenes via structure analysis.

IEEE transactions on cybernetics
Abnormal behavior detection in crowd scenes is continuously a challenge in the field of computer vision. For tackling this problem, this paper starts from a novel structure modeling of crowd behavior. We first propose an informative structural contex...

Does surface completion fail to support uncrowding?

Journal of vision
In crowding, perception of a target deteriorates in the presence of nearby elements. As the entire stimulus configuration across large parts of the visual field influences crowding and not just nearby elements, low-level explanations, such as local p...

Crowd Counting Using Meta-Test-Time Adaptation.

International journal of neural systems
Machine learning algorithms are commonly used for quickly and efficiently counting people from a crowd. Test-time adaptation methods for crowd counting adjust model parameters and employ additional data augmentation to better adapt the model to the s...

Exploring Hospital Overcrowding with an Explainable Time-to-Event Machine Learning Approach.

Studies in health technology and informatics
Emergency department (ED) overcrowding is a complex problem that is intricately linked with the operations of other hospital departments. Leveraging ED real-world production data provides a unique opportunity to comprehend this multifaceted problem h...

Crowding and attention in a framework of neural network model.

Journal of vision
In this article, I present a framework that would accommodate the classic ideas of visual information processing together with more recent computational approaches. I used the current knowledge about visual crowding, capacity limitations, attention, ...

A Gene Selection Method for Microarray Data Based on Binary PSO Encoding Gene-to-Class Sensitivity Information.

IEEE/ACM transactions on computational biology and bioinformatics
Traditional gene selection methods for microarray data mainly considered the features' relevance by evaluating their utility for achieving accurate predication or exploiting data variance and distribution, and the selected genes were usually poorly e...

A Novel Cluster Head Selection Algorithm Based on Fuzzy Clustering and Particle Swarm Optimization.

IEEE/ACM transactions on computational biology and bioinformatics
An important objective of wireless sensor network is to prolong the network life cycle, and topology control is of great significance for extending the network life cycle. Based on previous work, for cluster head selection in hierarchical topology co...