AIMC Topic: Animals

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Windy events detection in big bioacoustics datasets using a pre-trained Convolutional Neural Network.

The Science of the total environment
Passive Acoustic Monitoring (PAM), which involves using autonomous record units for studying wildlife behaviour and distribution, often requires handling big acoustic datasets collected over extended periods. While these data offer invaluable insight...

Exploring deep learning strategies for intervertebral disc herniation detection on veterinary MRI.

Scientific reports
Intervertebral Disc Herniation (IVDH) is a common spinal disease in dogs, significantly impacting their health, mobility, and overall well-being. This study initiates an effort to automate the detection and localization of IVDH lesions in veterinary ...

Inductive biases of neural network modularity in spatial navigation.

Science advances
The brain may have evolved a modular architecture for daily tasks, with circuits featuring functionally specialized modules that match the task structure. We hypothesize that this architecture enables better learning and generalization than architect...

Comparative Analysis of Milking and Behavior Characteristics of Multiparous and Primiparous Cows in Robotic Systems.

Anais da Academia Brasileira de Ciencias
Robotic milking systems are successful innovations in the development of dairy cattle. The objective of this study was to analyse the milking characteristics and behavior of dairy cows of different calving orders in "milk first" robotic milking syste...

Causality-inspired crop pest recognition based on Decoupled Feature Learning.

Pest management science
BACKGROUND: Ensuring the efficient recognition and management of crop pests is crucial for maintaining the balance in global agricultural ecosystems and ecological harmony. Deep learning-based methods have shown promise in crop pest recognition. Howe...

A comprehensive prediction system for silkworm acute toxicity assessment of environmental and in-silico pesticides.

Ecotoxicology and environmental safety
The excessive application and loss of pesticides poses a great risk to the ecosystem, and the environmental safety assessment of pesticides is time-consuming and expensive using traditional animal toxicity tests. In this work, a pesticide acute toxic...

A deep learning-based toolkit for 3D nuclei segmentation and quantitative analysis in cellular and tissue context.

Development (Cambridge, England)
We present a new set of computational tools that enable accurate and widely applicable 3D segmentation of nuclei in various 3D digital organs. We have developed an approach for ground truth generation and iterative training of 3D nuclear segmentation...

Automated identification and segmentation of urine spots based on deep-learning.

PeerJ
Micturition serves an essential physiological function that allows the body to eliminate metabolic wastes and maintain water-electrolyte balance. The urine spot assay (VSA), as a simple and economical assay, has been widely used in the study of mictu...

Evaluating machine learning algorithms to predict lameness in dairy cattle.

PloS one
Dairy cattle lameness represents one of the common concerns in intensive and commercial dairy farms. Lameness is characterized by gait-related behavioral changes in cows and multiple approaches are being utilized to associate these changes with lamen...

Prediction of Left Ventricle Pressure Indices Via a Machine Learning Approach Combining ECG, Pulse Oximetry, and Cardiac Sounds: a Preclinical Feasibility Study.

Journal of cardiovascular translational research
Heart failure (HF) is defined as the inability of the heart to meet body oxygen demand requiring an elevation in left ventricular filling pressures (LVP) to compensate. LVP increase can be assessed in the cardiac catheterization laboratory, but this ...