AIMC Topic: Environment

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The rise of intelligent matter.

Nature
Artificial intelligence (AI) is accelerating the development of unconventional computing paradigms inspired by the abilities and energy efficiency of the brain. The human brain excels especially in computationally intensive cognitive tasks, such as p...

A Subvision System for Enhancing the Environmental Adaptability of the Powered Transfemoral Prosthesis.

IEEE transactions on cybernetics
Visual information is indispensable to human locomotion in complex environments. Although amputees can perceive the environmental information by eyes, they cannot transmit the neural signals to prostheses directly. To augment human-prosthesis interac...

Robust Environmental Sound Recognition With Sparse Key-Point Encoding and Efficient Multispike Learning.

IEEE transactions on neural networks and learning systems
The capability for environmental sound recognition (ESR) can determine the fitness of individuals in a way to avoid dangers or pursue opportunities when critical sound events occur. It still remains mysterious about the fundamental principles of biol...

Decision Tree Algorithm Identifies Stroke Patients Likely Discharge Home After Rehabilitation Using Functional and Environmental Predictors.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND AND PURPOSE: The importance of environmental factors for stroke patients to achieve home discharge was not scientifically proven. There are limited studies on the application of the decision tree algorithm with various functional and envir...

Domain randomization-enhanced deep learning models for bird detection.

Scientific reports
Automatic bird detection in ornithological analyses is limited by the accuracy of existing models, due to the lack of training data and the difficulties in extracting the fine-grained features required to distinguish bird species. Here we apply the d...

Deep learning for automated analysis of fish abundance: the benefits of training across multiple habitats.

Environmental monitoring and assessment
Environmental monitoring guides conservation and is particularly important for aquatic habitats which are heavily impacted by human activities. Underwater cameras and uncrewed devices monitor aquatic wildlife, but manual processing of footage is a si...

Quantifying the usage of small public spaces using deep convolutional neural network.

PloS one
Small public spaces are the key built environment elements that provide venues for various of activities. However, existing measurements or approaches could not efficiently and effectively quantify how small public spaces are being used. In this pape...

Intuitionistic Fuzzy Hierarchical Multi-Criteria Decision Making for Evaluating Performances of Low-Carbon Tourism Scenic Spots.

International journal of environmental research and public health
Low-carbon tourism is an effective solution to cope with the goal conflict between developing tourist economy and responding to carbon emission reduction and ecological environment protection. Tourism scenic spots are important carriers of tourist ac...

[The use of artificial neural networks to classify the social vulnerability of municipalities in Rio Grande do Norte State, Brazil].

Cadernos de saude publica
The objective was to apply artificial neural networks to classify municipalities (counties) in Rio Grande do Norte State, Brazil, according to their social vulnerability. This was an ecological study using 17 variables that reflected epidemiological,...

Multilevel approach to male fertility by machine learning highlights a hidden link between haematological and spermatogenetic cells.

Andrology
BACKGROUND: Male infertility represents a complex clinical condition requiring an accurate multilevel assessment, in which machine learning technology, combining large data series in non-linear and highly interactive ways, could be innovatively appli...