CowScreeningDB：用于奶牛跛行检测的公开基准数据集
CowScreeningDB: A public benchmark dataset for lameness detection in dairy cows
AI总结：
针对奶牛跛行检测缺乏公开数据集的问题，本文提出CowScreeningDB多传感器基准数据集，并共享基于原始感官数据的机器学习分类方法，验证传感器数据与跛行的关联。
摘要：
跛行是影响奶牛的最昂贵的病理问题之一。通常由训练有素的兽医临床医生通过观察步态对称性或步态参数（如实时步数）等特征进行评估。随着人工智能的发展，已经提出了各种模块化系统，以尽量减少跛行评估中的主观性。然而，其开发的主要限制是缺乏公开数据集，目前这些数据集要么是商业性的，要么是私人持有的。为了解决这一限制，我们引入了CowScreeningDB，该数据集是使用感官数据创建的。该数据集来自西班牙大加那利岛一个奶牛场的43头奶牛。它由一个多传感器数据集组成，该数据集基于在奶牛正常日常活动中使用Apple Watch 6收集的数据。得益于采集环境、采样技术、传感器信息以及用于数据转换和存储的应用程序，该数据集具有透明性。这种数据的透明性因此可以用于进一步开发奶牛跛行检测技术，并可以进行客观比较。除了公开共享数据集外，我们还共享了一种机器学习技术，该技术通过使用原始感官数据将奶牛分类为健康和跛行。从而验证了主要目标，即建立传感器数据与跛行之间的关系。
英文摘要：
Lameness is one of the costliest pathological problems affecting dairy animals. It is usually assessed by trained veterinary clinicians who observe features such as gait symmetry or gait parameters as step counts in real-time. With the development of artificial intelligence, various modular systems have been proposed to minimize subjectivity in lameness assessment. However, the major limitation in their development is the unavailability of a public dataset which is currently either commercial or privately held. To tackle this limitation, we have introduced CowScreeningDB which was created using sensory data. This dataset was sourced from 43 cows at a dairy located in Gran Canaria, Spain. It consists of a multi-sensor dataset built on data collected using an Apple Watch 6 during the normal daily routine of a dairy cow. Thanks to the collection environment, sampling technique, information regarding the sensors, the applications used for data conversion and storage make the dataset a transparent one. This transparency of data can thus be used for further development of techniques for lameness detection for dairy cows which can be objectively compared. Aside from the public sharing of the dataset, we have also shared a machine-learning technique which classifies the caws in healthy and lame by using the raw sensory data. Hence validating the major objective which is to establish the relationship between sensor data and lameness.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
