Stall Number Detection of Cow Teats Key Frames

TL;DR

This paper introduces the CowStallNumbers dataset for cow stall number detection, and demonstrates that fine-tuning ResNet34 with data augmentation achieves high accuracy in recognizing stall numbers.

Contribution

The paper provides a new dataset for cow stall number detection and evaluates a deep learning approach with data augmentation for improved accuracy.

Findings

92% accuracy in stall number recognition

40.1% IoU score in stall number position prediction

Dataset contains 1303 images with stall numbers from 0 to 60

Abstract

In this paper, we present a small cow stall number dataset named CowStallNumbers, which is extracted from cow teat videos with the goal of advancing cow stall number detection. This dataset contains 1042 training images and 261 test images with the stall number ranging from 0 to 60. In addition, we fine-tuned a ResNet34 model and augmented the dataset with the random crop, center crop, and random rotation. The experimental result achieves a 92% accuracy in stall number recognition and a 40.1% IoU score in stall number position prediction.