Deep learning-based animal activity recognition with wearable sensors: Overview, challenges, and future directions
Animal behavior, as one of the most crucial indicators of animal health and welfare, provides
rich insights into animal physical and mental states. Automated animal activity recognition …
rich insights into animal physical and mental states. Automated animal activity recognition …
Machine learning-based sensor data fusion for animal monitoring: Scoping review
CA Aguilar-Lazcano, IE Espinosa-Curiel… - Sensors, 2023 - mdpi.com
The development of technology, such as the Internet of Things and artificial intelligence, has
significantly advanced many fields of study. Animal research is no exception, as these …
significantly advanced many fields of study. Animal research is no exception, as these …
Automated identification of chicken distress vocalizations using deep learning models
The annual global production of chickens exceeds 25 billion birds, which are often housed
in very large groups, numbering thousands. Distress calling triggered by various sources of …
in very large groups, numbering thousands. Distress calling triggered by various sources of …
FedAAR: A novel federated learning framework for animal activity recognition with wearable sensors
Simple Summary Automated animal activity recognition has achieved great success due to
the recent advances in deep learning, allowing staff to identify variations in the animal …
the recent advances in deep learning, allowing staff to identify variations in the animal …
A cognitive-driven ordinal preservation for multimodal imbalanced brain disease diagnosis
Q Zhu, T Zhu, R Zhang, H Ye, K Sun… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The multimodal imbalanced data learning problems are becoming increasingly common in
the real world, especially in brain disease diagnosis. Although multimodal data provide …
the real world, especially in brain disease diagnosis. Although multimodal data provide …
Unsupervised Domain Adaptation for Mitigating Sensor Variability and Interspecies Heterogeneity in Animal Activity Recognition
Simple Summary This study aimed to improve animal activity recognition (AAR) using
wearable sensor data, which often faces challenges due to sensor variability and individual …
wearable sensor data, which often faces challenges due to sensor variability and individual …
Time-series-based feature selection and clustering for equine activity recognition using accelerometers
With over 16 million horses worldwide and nearly 60000 sport horses registered to the
International Federation for Equestrian Sports database, tracking the activities and …
International Federation for Equestrian Sports database, tracking the activities and …
A teacher-to-student information recovery method toward energy-efficient animal activity recognition at low sampling rates
Automated animal activity recognition (AAR) has advanced greatly through recent advances
in sensing technologies and deep learning, and improved livestock management efficiency …
in sensing technologies and deep learning, and improved livestock management efficiency …
Transformer-based Dog Behavior Classification with Motion Sensors
B Or - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
This article deals with classifying dog behavior using motion sensors, leveraging a
transformer-based deep neural network (DNN) model. Understanding dog behavior is …
transformer-based deep neural network (DNN) model. Understanding dog behavior is …
CKSP: Cross-species Knowledge Sharing and Preserving for Universal Animal Activity Recognition
Deep learning techniques are dominating automated animal activity recognition (AAR) tasks
with wearable sensors due to their high performance on large-scale labelled data. However …
with wearable sensors due to their high performance on large-scale labelled data. However …