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Crowding

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A collaborative neurodynamic approach to global and combinatorial optimization.

Neural networks : the official journal of the International Neural Network Society
In this paper, a collaborative neurodynamic optimization approach is proposed for global and combinatorial optimization. First, a combinatorial optimization problem is reformulated as a global optimization problem. Second, a neurodynamic optimization...

Crowding reveals fundamental differences in local vs. global processing in humans and machines.

Vision research
Feedforward Convolutional Neural Networks (ffCNNs) have become state-of-the-art models both in computer vision and neuroscience. However, human-like performance of ffCNNs does not necessarily imply human-like computations. Previous studies have sugge...

Crowding in humans is unlike that in convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society
Object recognition is a primary function of the human visual system. It has recently been claimed that the highly successful ability to recognise objects in a set of emergent computer vision systems-Deep Convolutional Neural Networks (DCNNs)-can form...

Early short-term prediction of emergency department length of stay using natural language processing for low-acuity outpatients.

The American journal of emergency medicine
BACKGROUND: Low-acuity outpatients constitute the majority of emergency department (ED) patients, and these patients often experience an unpredictable length of stay (LOS). Effective LOS prediction might improve the quality of ED care and reduce ED c...

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, ...

Crowd density estimation using deep learning for Hajj pilgrimage video analytics.

F1000Research
BACKGROUND: This paper focuses on advances in crowd control study with an emphasis on high-density crowds, particularly Hajj crowds. Video analysis and visual surveillance have been of increasing importance in order to enhance the safety and security...

Graph Regularized Flow Attention Network for Video Animal Counting From Drones.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, we propose a large-scale video based animal counting dataset collected by drones (AnimalDrone) for agriculture and wildlife protection. The dataset consists of two subsets, i.e., PartA captured on site by drones and PartB collected fro...

Abnormal Activity Recognition from Surveillance Videos Using Convolutional Neural Network.

Sensors (Basel, Switzerland)
UNLABELLED: Background and motivation: Every year, millions of Muslims worldwide come to Mecca to perform the Hajj. In order to maintain the security of the pilgrims, the Saudi government has installed about 5000 closed circuit television (CCTV) came...

Context-Aware Multi-Scale Aggregation Network for Congested Crowd Counting.

Sensors (Basel, Switzerland)
In this paper, we propose a context-aware multi-scale aggregation network named CMSNet for dense crowd counting, which effectively uses contextual information and multi-scale information to conduct crowd density estimation. To achieve this, a context...