Models
MobileNet SSD v2 vs. YOLOv4 Tiny

MobileNet SSD v2 vs. YOLOv4 Tiny

Both MobileNet SSD v2 and YOLOv4 Tiny are commonly used in computer vision projects. Below, we compare and contrast MobileNet SSD v2 and YOLOv4 Tiny.

Models

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MobileNet SSD v2

This architecture provides good realtime results on limited compute. It's designed to run in realtime (30 frames per second) even on mobile devices.
Learn more about MobileNet SSD v2
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YOLOv4 Tiny

The tiny and fast version of YOLOv4 - good for training and deployment on limited compute resources, and getting a feel for your dataset
Learn more about YOLOv4 Tiny
Model Type
Object Detection
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
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ResNet-D, YOLO
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Frameworks
TensorFlow 1.5
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Darknet
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub
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View Repo
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View Repo
GitHub Stars
81+
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License
MIT
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YOLO
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Paper
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View Paper
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View Paper
Training Notebook
Train on Colab
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Train on Colab
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Deploy Model
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Deploy with Roboflow
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Deploy with Roboflow
Compare Alternatives
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Compare MobileNet SSD v2 and YOLOv4 Tiny with Autodistill

Compare MobileNet SSD v2 vs. YOLOv4 Tiny

Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.

COCO can detect 80 common objects, including cats, cell phones, and cars.