AIMC Topic: Cats
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Adaptive Modular Convolutional Neural Network for Image Recognition.
Sensors (Basel, Switzerland)
Jul 22, 2022
Image recognition has long been one of the research hotspots in computer vision tasks. The development of deep learning is rapid in recent years, and convolutional neural networks usually need to be designed with fixed resources. If sufficient resour...
Deep learning in veterinary medicine, an approach based on CNN to detect pulmonary abnormalities from lateral thoracic radiographs in cats.
Scientific reports
Jul 6, 2022
Thoracic radiograph (TR) is a complementary exam widely used in small animal medicine which requires a sharp analysis to take full advantage of Radiographic Pulmonary Pattern (RPP). Although promising advances have been made in deep learning for vete...
Integrative measurement analysis via machine learning descriptor selection for investigating physical properties of biopolymers in hairs.
Scientific reports
Dec 21, 2021
Integrative measurement analysis of complex subjects, such as polymers is a major challenge to obtain comprehensive understanding of the properties. In this study, we describe analytical strategies to extract and selectively associate compositional i...
Quantifying finer-scale behaviours using self-organising maps (SOMs) to link accelerometery signatures with behavioural patterns in free-roaming terrestrial animals.
Scientific reports
Jun 30, 2021
Collecting quantitative information on animal behaviours is difficult, especially from cryptic species or species that alter natural behaviours under observation. Using harness-mounted tri-axial accelerometers free-roaming domestic cats (Felis Catus)...
The CPGs for Limbed Locomotion-Facts and Fiction.
International journal of molecular sciences
May 30, 2021
The neuronal networks that generate locomotion are well understood in swimming animals such as the lamprey, zebrafish and tadpole. The networks controlling locomotion in tetrapods remain, however, still enigmatic with an intricate motor pattern requi...
Further evaluation and validation of the VETSCAN IMAGYST: in-clinic feline and canine fecal parasite detection system integrated with a deep learning algorithm.
Parasites & vectors
Jan 29, 2021
BACKGROUND: Fecal examinations in pet cats and dogs are key components of routine veterinary practice; however, their accuracy is influenced by diagnostic methodologies and the experience level of personnel performing the tests. The VETSCAN IMAGYST s...
Infrared and visible image fusion method of dual NSCT and PCNN.
PloS one
Sep 18, 2020
To solve the problem that the details of fusion images are not retained well and the information of feature targets is incomplete, we proposed a new fusion method of infrared (IR) and visible (VI) image-IR and VI image fusion method of dual non-subsa...
Robot companion cats for people at home with dementia: A qualitative case study on companotics.
Dementia (London, England)
Jul 16, 2020
The use of robot companion pets for people in care homes has been extensively studied. The results are largely positive and suggest that they are valuable in enhancing wellbeing, communication and behavioural aspects. However, there has been little r...
Evaluation of the VETSCAN IMAGYST: an in-clinic canine and feline fecal parasite detection system integrated with a deep learning algorithm.
Parasites & vectors
Jul 11, 2020
BACKGROUND: Fecal examination is an important component of routine companion animal wellness exams. Sensitivity and specificity of fecal examinations, however, are influenced by sample preparation methodologies and the level of training and experienc...
Making Sense of Pharmacovigilance and Drug Adverse Event Reporting: Comparative Similarity Association Analysis Using AI Machine Learning Algorithms in Dogs and Cats.
Topics in companion animal medicine
Sep 30, 2019
Drug-associated adverse events cause approximately 30 billion dollars a year of added health care expense, along with negative health outcomes including patient death. This constitutes a major public health concern. The US Food and Drug Administratio...
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