AIMC Topic: Housing

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Identifying Informal Settlements Using Contourlet Assisted Deep Learning.

Sensors (Basel, Switzerland)
As the global urban population grows due to the influx of migrants from rural areas, many cities in developing countries face the emergence and proliferation of unplanned and informal settlements. However, even though the rise of unplanned developmen...

Do street-level scene perceptions affect housing prices in Chinese megacities? An analysis using open access datasets and deep learning.

PloS one
Many studies have explored the relationship between housing prices and environmental characteristics using the hedonic price model (HPM). However, few studies have deeply examined the impact of scene perception near residential units on housing price...

Predicting the concentration of indoor culturable fungi using a kernel-based extreme learning machine (K-ELM).

International journal of environmental health research
Indoor fungal is of great significance for human health. The kernel-based extreme learning machine is employed to determine the most important parameters for predicting the concentration of indoor culturable fungi (ICF). For model training and statis...

Measuring social, environmental and health inequalities using deep learning and street imagery.

Scientific reports
Cities are home to an increasing majority of the world's population. Currently, it is difficult to track social, economic, environmental and health outcomes in cities with high spatial and temporal resolution, needed to evaluate policies regarding ur...

Use of Machine Learning in the Analysis of Indoor ELF MF Exposure in Children.

International journal of environmental research and public health
Characterization of children exposure to extremely low frequency (ELF) magnetic fields is an important issue because of the possible correlation of leukemia onset with ELF exposure. Cluster analysis-a Machine Learning approach-was applied on personal...

Information-Based Boundary Equilibrium Generative Adversarial Networks with Interpretable Representation Learning.

Computational intelligence and neuroscience
This paper describes a new image generation algorithm based on generative adversarial network. With an information-theoretic extension to the autoencoder-based discriminator, this new algorithm is able to learn interpretable representations from the ...

Predicting residential structures from open source remotely enumerated data using machine learning.

PloS one
Having accurate maps depicting the locations of residential buildings across a region benefits a range of sectors. This is particularly true for public health programs focused on delivering services at the household level, such as indoor residual spr...

The Association of Urban Greenness and Walking Behavior: Using Google Street View and Deep Learning Techniques to Estimate Residents' Exposure to Urban Greenness.

International journal of environmental research and public health
Many studies have established that urban greenness is associated with better health outcomes. Yet most studies assess urban greenness with overhead-view measures, such as park area or tree count, which often differs from the amount of greenness perce...

Health management and pattern analysis of daily living activities of people with dementia using in-home sensors and machine learning techniques.

PloS one
The number of people diagnosed with dementia is expected to rise in the coming years. Given that there is currently no definite cure for dementia and the cost of care for this condition soars dramatically, slowing the decline and maintaining independ...

Controlling robots in the home: Factors that affect the performance of novice robot operators.

Applied ergonomics
For robots to successfully integrate into everyday life, it is important that they can be effectively controlled by laypeople. However, the task of manually controlling mobile robots can be challenging due to demanding cognitive and sensorimotor requ...