10 citations · 46 across the 12 of their papers we have counts for
4 papers · 1 filter
Machine Learning Approaches to Predict and Detect Early-Onset of Digital Dermatitis in Dairy Cows using Sensor Data
Jennifer Magana, Dinu Gavojdian, Yakir Menachem +3
The aim of this study was to employ machine learning algorithms based on sensor behavior data for (1) early-onset detection of digital dermatitis (DD); and (2) DD prediction in dai…
Digitally-Enhanced Dog Behavioral Testing: Getting Help from the Machine
Nareed Farhat, Teddy Lazebnik, Joke Monteny +4
The assessment of behavioral traits in dogs is a well-studied challenge due to its many practical applications such as selection for breeding, prediction of working aptitude, chanc…
BovineTalk: Machine Learning for Vocalization Analysis of Dairy Cattle under Negative Affective States
Dinu Gavojdian, Teddy Lazebnik, Madalina Mincu +3
There is a critical need to develop and validate non-invasive animal-based indicators of affective states in livestock species, in order to integrate them into on-farm assessment p…
CatFLW: Cat Facial Landmarks in the Wild Dataset
George Martvel, Nareed Farhat, Ilan Shimshoni +1
Animal affective computing is a quickly growing field of research, where only recently first efforts to go beyond animal tracking into recognizing their internal states, such as pa…