AIMC Topic: Animals

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Application of 3D Animation Cluster System Based on Artificial Intelligence and Machine Learning.

Computational intelligence and neuroscience
In many living phenomena, the behavior of social animals (such as ants, fish stocks, and birds) has attracted great attention, and many theories and models have emerged to simulate the behavior of biological communities. These studies are important i...

Revealing the real-time diversity and abundance of small mammals by using an Intelligent Animal Monitoring System (IAMS).

Integrative zoology
It is challenging to reveal the real-time spatio-temporal change of diversity and abundance of animals in natural systems by using traditional methods. The rapid advancement of new technologies such as the Internet of Things, artificial intelligence,...

Sharing Rewards Undermines Coordinated Hunting.

Journal of computational biology : a journal of computational molecular cell biology
Coordinated hunting is widely observed in animals, and sharing rewards is often considered a major incentive for its success. While current theories about the role played by sharing in coordinated hunting are based on correlational evidence, we revea...

Deep learning for necrosis detection using canine perivascular wall tumour whole slide images.

Scientific reports
Necrosis seen in histopathology Whole Slide Images is a major criterion that contributes towards scoring tumour grade which then determines treatment options. However conventional manual assessment suffers from inter-operator reproducibility impactin...

A Multiobjective Hybrid Optimization Algorithm for Path Planning of Coal Mine Patrol Robot.

Computational intelligence and neuroscience
In the complex underground environment, the paths planned for coal mine patrol robot are often too long and unsmooth under the influence of low visibility and poor road conditions. To solve the problems, this paper improves the hybrid algorithm betwe...

Bayesian statistics-guided label refurbishment mechanism: Mitigating label noise in medical image classification.

Medical physics
PURPOSE: Deep neural networks (DNNs) have been widely applied in medical image classification, benefiting from its powerful mapping capability among medical images. However, these existing deep learning-based methods depend on an enormous amount of c...

Latent space of a small genetic network: Geometry of dynamics and information.

Proceedings of the National Academy of Sciences of the United States of America
The high-dimensional character of most biological systems presents genuine challenges for modeling and prediction. Here we propose a neural network-based approach for dimensionality reduction and analysis of biological gene expression data, using, as...

Codon Optimization Using a Recurrent Neural Network.

Journal of computational biology : a journal of computational molecular cell biology
Codon optimization of a DNA sequence can significantly increase efficiency of protein expression, reducing the cost to manufacture biologic pharmaceuticals. Although directed methods based on such factors as codon usage bias and GC nucleotide content...

Designing grazing susceptibility to land degradation index (GSLDI) in hilly areas.

Scientific reports
Evaluation of grazing impacts on land degradation processes is a difficult task due to the heterogeneity and complex interacting factors involved. In this paper, we designed a new methodology based on a predictive index of grazing susceptibility to l...

Face identity coding in the deep neural network and primate brain.

Communications biology
A central challenge in face perception research is to understand how neurons encode face identities. This challenge has not been met largely due to the lack of simultaneous access to the entire face processing neural network and the lack of a compreh...