Creating intelligent systems capable of recognizing emotions is a difficult task, especially when looking at emotions in animals. This paper describes the process of designing a “proof of concept” system to recognize emotions in horses. This system is formed by two elements, a detector and a model. The detector is a fast region-based convolutional neural network that detects horses in an image. The model is a convolutional neural network that predicts the emotions of those horses. These two elements were trained with multiple images of horses until they achieved high accuracy in their tasks. In total, 400 images of horses were collected and labeled to train both the detector and the model while 40 were used to validate the system. Once the two components were validated, they were combined into a testable system that would detect equine emotions based on established behavioral ethograms indicating emotional affect through the head, neck, ear, muzzle, and eye position. The system showed an accuracy of 80% on the validation set, demonstrating that it is possible to predict emotions in animals using autonomous intelligent systems. Such a system has multiple applications including further studies in the growing field of animal emotions as well as in the veterinary field to determine the physical welfare of horses or other livestock.
This article briefly describes different conditioning techniques used to help understand learning in farm livestock and economically important animals. A basic overview of conditioning is included along with the importance of different conditioning methods, associative and non-associative learning, and how these principles apply to chickens, horses, cows, goats, pigs, and sheep. Additional information on learning theory specific for each animal is also provided. Keywords: cattle; classical; conditioning; goats; horses; operant; pigs; sheep; training.
ResumoEste artigo descreve brevemente diferentes técnicas de condicionamento usadas para ajudar a compreender a aprendizagem em animas de criação e animais economicamente importantes. Uma visão geral básica de condicionamento está incluída juntamente com a importância de diferentes métodos de condicionamento, aprendizagens associativas e não-associativas e como esses princípios se aplicam para as galinhas, cavalos, vacas, suínos, caprinos e ovinos. Informações adicionais sobre a teoria de aprendizagem específica para cada animal também são fornecidas.
The nomenclature used to describe animals working in roles supporting people can be confusing. The same term may be used to describe different roles, or two terms may mean the same thing. This confusion is evident among researchers, practitioners, and end users. Because certain animal roles are provided with legal protections and/or government-funding support in some jurisdictions, it is necessary to clearly define the existing terms to avoid confusion. The aim of this paper is to provide operationalized definitions for nine terms, which would be useful in many world regions: “assistance animal”, “companion animal”, “educational/school support animal”, “emotional support animal”, “facility animal”, “service animal”, “skilled companion animal”, “therapy animal”, and “visiting/visitation animal”. At the International Society for Anthrozoology (ISAZ) conferences in 2018 and 2020, over 100 delegates participated in workshops to define these terms, many of whom co-authored this paper. Through an iterative process, we have defined the nine terms and explained how they differ from each other. We recommend phasing out two terms (i.e., “skilled companion animal” and “service animal”) due to overlap with other terms that could potentially exacerbate confusion. The implications for several regions of the world are discussed.
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