AIMC Topic: Animals

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Reward-predictive representations generalize across tasks in reinforcement learning.

PLoS computational biology
In computer science, reinforcement learning is a powerful framework with which artificial agents can learn to maximize their performance for any given Markov decision process (MDP). Advances over the last decade, in combination with deep neural netwo...

Virgin Coconut Oil-Induced Neuroprotection in Lipopolysaccharide-Challenged Rats is Mediated, in Part, Through Cholinergic, Anti-Oxidative and Anti-Inflammatory Pathways.

Journal of dietary supplements
Neuroinflammation is associated with neuronal cell death and could lead to chronic neurodegeneration. This study investigated the neuroprotective potential of virgin coconut oil (VCO) against lipopolysaccharide (LPS)-induced cytotoxicity of neuroblas...

A Machine Learning Approach in Analyzing Bioaccumulation of Heavy Metals in Turbot Tissues.

Molecules (Basel, Switzerland)
Metals are considered to be one of the most hazardous substances due to their potential for accumulation, magnification, persistence, and wide distribution in water, sediments, and aquatic organisms. Demersal fish species, such as turbot (), are acce...

Performance vs. competence in human-machine comparisons.

Proceedings of the National Academy of Sciences of the United States of America
Does the human mind resemble the machines that can behave like it? Biologically inspired machine-learning systems approach "human-level" accuracy in an astounding variety of domains, and even predict human brain activity-raising the exciting possibil...

Using machine learning to understand the implications of meteorological conditions for fish kills.

Scientific reports
Fish kills, often caused by low levels of dissolved oxygen (DO), involve with complex interactions and dynamics in the environment. In many places the precise cause of massive fish kills remains uncertain due to a lack of continuous water quality mon...

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...

The covariance perceptron: A new paradigm for classification and processing of time series in recurrent neuronal networks.

PLoS computational biology
Learning in neuronal networks has developed in many directions, in particular to reproduce cognitive tasks like image recognition and speech processing. Implementations have been inspired by stereotypical neuronal responses like tuning curves in the ...

Spage2vec: Unsupervised representation of localized spatial gene expression signatures.

The FEBS journal
Investigations of spatial cellular composition of tissue architectures revealed by multiplexed in situ RNA detection often rely on inaccurate cell segmentation or prior biological knowledge from complementary single-cell sequencing experiments. Here,...

Application of deep learning in genomics.

Science China. Life sciences
In recent years, deep learning has been widely used in diverse fields of research, such as speech recognition, image classification, autonomous driving and natural language processing. Deep learning has showcased dramatically improved performance in ...