Table 4. Summary of pig disease detection and tracking using RGB imaging and machine learning algorithms

Camera type	Detection type	Method / algorithm	Accuracy	Reference
FL3-U3-88S2C-C	Diseases, posture, and tracking	PigMS R–CNN	93.0	[85]
Kinect v2		Faster R–CNN	87.1	[84]
Kinect v2		YOLO	91.96	[86]
Kinect RGB		Faster R–CNN, YOLO	98.9	[87]
DS-2CD1321D-I		FCN+VGG16	97.6	[88]
DS-2CD1321D-I		FCN+VGG16	96.4	[89]
IFM O3D313	Locomotion	RF + KNN	–	[90]
Kinect v2		Faster R–CNN+ Deep SORT	90.1	[91]
Dahua IPC-HFW1230S-S4	Body weight	Mask R–CNN, PCP, MLP	97.4	[92]
Intel Real Sense D435		PointNet	94.2	[93]
Basler TOF 640		YOLOv5 + MobilenetV3	97.8	[94]
Kinect camera		Structure from motion (SfM)	–	[81]
Kinect camera		CNN	–	[84]

CNN, convolutional neural network; YOLO, you only look once; FCN, fully convolutional network; VGG16, Visual Geometry Group Network having 16 layers.