MobileNet V2 Classification vs. YOLOv4

Both MobileNet V2 Classification and YOLOv4 Darknet are commonly used in computer vision projects. Below, we compare and contrast MobileNet V2 Classification and YOLOv4 Darknet.

Models

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.

Learn more about MobileNet V2 Classification

YOLOv4 Darknet

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 Darknet.

Learn more about YOLOv4 Darknet

Model Type

Classification

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Object Detection

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Model Features

Item 1 Info

Item 2 Info

Architecture

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YOLO

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Frameworks

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Darknet

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Annotation Format

Instance Segmentation

Instance Segmentation

GitHub

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GitHub Stars

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License

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YOLO

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Paper

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Training Notebook

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Deploy Model

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Deploy with Roboflow

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Deploy with Roboflow

Compare MobileNet V2 Classification and YOLOv4 Darknet with Autodistill

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MobileNet V2 Classification vs. YOLOv4

MobileNet V2 Classification vs. YOLOv4

.

Both

MobileNet V2 Classification

and

YOLOv4 Darknet

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

MobileNet V2 Classification

and

YOLOv4 Darknet

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

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 Darknet

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 Darknet.

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 Darknet

Compare MobileNet V2 Classification to other models

Compare YOLOv4 Darknet to other models

YOLOv8 Instance Segmentation

YOLOv7 Instance Segmentation

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