MobileNet V2 Classification vs. YOLOv4 PyTorch: Compared and Contrasted

Models

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MobileNet V2 Classification vs. YOLOv4 PyTorch

Both

MobileNet V2 Classification

and

YOLOv4 PyTorch

are commonly used in computer vision projects. Below, we compare and contrast

MobileNet V2 Classification

and

YOLOv4 PyTorch

	MobileNet V2 Classification	YOLOv4 PyTorch
Date of Release
Model Type	Classification	Object Detection
Architecture		YOLO
GitHub Stars		4200

MobileNet V2 Classification

MobileNet is a GoogleAI model well-suited for on-device, real-time classification (distinct from MobileNetSSD, Single Shot Detector). This implementation leverages transfer learning from ImageNet to your dataset.

How to Augment How to Label How to Plot Predictions How to Filter Predictions How to Create a Confusion Matrix

YOLOv4 PyTorch

YOLOv4 has emerged as the best real time object detection model. YOLOv4 carries forward many of the research contributions of the YOLO family of models along with new modeling and data augmentation techniques. This implementation is in PyTorch.

How to Augment How to Label How to Plot Predictions How to Filter Predictions How to Create a Confusion Matrix

Learn more about MobileNet V2 Classification

Learn more about YOLOv4 PyTorch