AIMC Topic: Animals

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Rapid identification of counterfeited beef using deep learning-aided spectroscopy: Detecting colourant and curing agent adulteration.

Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association
The adulteration of meat products using colourants and curing agents has heightened concerns over food safety, thereby necessitating the development of advanced detection methods. This study introduces a deep-learning-based spectroscopic method for s...

A Survey of Deep Learning Techniques for Underwater Image Classification.

IEEE transactions on neural networks and learning systems
In recent years, there has been an enormous interest in using deep learning to classify underwater images to identify various objects, such as fishes, plankton, coral reefs, seagrass, submarines, and gestures of sea divers. This classification is ess...

Common knowledge processing patterns in networks of different systems.

PloS one
Knowledge processing has patterns which can be found in biological neuron activity and artificial neural networks. The work explores whether an underlying structure exists for knowledge which crosses domains. The results show common data processing p...

Based on the multi-scale information sharing network of fine-grained attention for agricultural pest detection.

PloS one
It is of great significance to identify the pest species accurately and control it effectively to reduce the loss of agricultural products. The research results of this project will provide theoretical basis for preventing and controlling the spread ...

Reconstructing computational system dynamics from neural data with recurrent neural networks.

Nature reviews. Neuroscience
Computational models in neuroscience usually take the form of systems of differential equations. The behaviour of such systems is the subject of dynamical systems theory. Dynamical systems theory provides a powerful mathematical toolbox for analysing...

Predicting Plant miRNA-lncRNA Interactions via a Deep Learning Method.

IEEE transactions on nanobioscience
In recent years, due to the contribution to elucidating the functional mechanisms of miRNAs and lncRNAs, the research on miRNA-lncRNA interaction prediction has increased exponentially. However, the prediction research is challenging in bioinformatic...

DensePPI: A Novel Image-Based Deep Learning Method for Prediction of Protein-Protein Interactions.

IEEE transactions on nanobioscience
Protein-protein interactions (PPI) are crucial for understanding the behaviour of living organisms and identifying disease associations. This paper proposes DensePPI, a novel deep convolution strategy applied to the 2D image map generated from the in...

Fractals and artificial intelligence to decrypt ideography and understand the evolution of language.

The Behavioral and brain sciences
Self-sufficient ideographies are rare because they are stifled by the issue of standardization. Similar issues arise with abstract art or drawings created by young children or great apes. We propose that mathematical indices and artificial intelligen...

Deep learning for fast denoising filtering in ultrasound localization microscopy.

Physics in medicine and biology
Addition of a denoising filter step in ultrasound localization microscopy (ULM) has been shown to effectively reduce the error localizations of microbubbles (MBs) and achieve resolution improvement for super-resolution ultrasound (SR-US) imaging. How...

Natural variability in bee brain size and symmetry revealed by micro-CT imaging and deep learning.

PLoS computational biology
Analysing large numbers of brain samples can reveal minor, but statistically and biologically relevant variations in brain morphology that provide critical insights into animal behaviour, ecology and evolution. So far, however, such analyses have req...