AIMC Topic: Animals

Clear Filters Showing 4931 to 4940 of 8866 articles

Experimentally revealed stochastic preferences for multicomponent choice options.

Journal of experimental psychology. Animal learning and cognition
Realistic, everyday rewards contain multiple components. An apple has taste and size. However, we choose in single dimensions, simply preferring some apples to others. How can such single-dimensional preference relationships refer to multicomponent c...

Revealing architectural order with quantitative label-free imaging and deep learning.

eLife
We report quantitative label-free imaging with phase and polarization (QLIPP) for simultaneous measurement of density, anisotropy, and orientation of structures in unlabeled live cells and tissue slices. We combine QLIPP with deep neural networks to ...

Machine learning for modeling animal movement.

PloS one
Animal movement drives important ecological processes such as migration and the spread of infectious disease. Current approaches to modeling animal tracking data focus on parametric models used to understand environmental effects on movement behavior...

Automatic robot-world calibration in an optical-navigated surgical robot system and its application for oral implant placement.

International journal of computer assisted radiology and surgery
PURPOSE: Robot-world calibration, used to precisely determine the spatial relation between optical tracker and robot, is regarded as an essential step for optical-navigated surgical robot system to improve the surgical accuracy. However, these method...

Deep learning for population size history inference: Design, comparison and combination with approximate Bayesian computation.

Molecular ecology resources
For the past decades, simulation-based likelihood-free inference methods have enabled researchers to address numerous population genetics problems. As the richness and amount of simulated and real genetic data keep increasing, the field has a strong ...

An intelligent way for discerning plastics at the shorelines and the seas.

Environmental science and pollution research international
Irrespective of how plastics litter the coastline or enter the sea, they pose a major threat to birds and marine life alike. In this study, an artificial intelligence tool was used to create an image classifier based on a convolutional neural network...

Deep learning-based behavioral analysis reaches human accuracy and is capable of outperforming commercial solutions.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
To study brain function, preclinical research heavily relies on animal monitoring and the subsequent analyses of behavior. Commercial platforms have enabled semi high-throughput behavioral analyses by automating animal tracking, yet they poorly recog...

Spiking Neural P Systems with Delay on Synapses.

International journal of neural systems
Based on the feature and communication of neurons in animal neural systems, spiking neural P systems (SN P systems) were proposed as a kind of powerful computing model. Considering the length of axons and the information transmission speed on synapse...

lncRNA_Mdeep: An Alignment-Free Predictor for Distinguishing Long Non-Coding RNAs from Protein-Coding Transcripts by Multimodal Deep Learning.

International journal of molecular sciences
Long non-coding RNAs (lncRNAs) play crucial roles in diverse biological processes and human complex diseases. Distinguishing lncRNAs from protein-coding transcripts is a fundamental step for analyzing the lncRNA functional mechanism. However, the exp...

Using an ontology of the human cardiovascular system to improve the classification of histological images.

Scientific reports
The advantages of automatically recognition of fundamental tissues using computer vision techniques are well known, but one of its main limitations is that sometimes it is not possible to classify correctly an image because the visual information is ...