Product
Solutions
Resources
Pricing
Docs
Talk to SalesSign in
Models
MobileNet SSD v2 vs. YOLOv3 Keras

Explore Models

By Task
All Models (32)Object Detection Models (19)Classification Models (7)Instance Segmentation Models (3)Semantic Segmentation Models (1)
By Feature
Foundation Vision ModelsMultimodal Vision ModelsImage Embedding ModelsReal Time Vision ModelsZero-Shot Detection ModelsOptimal for Edge Deployment

MobileNet SSD v2 vs. YOLOv3 Keras

Both

MobileNet SSD v2

and

YOLOv3 Keras

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

MobileNet SSD v2

and

YOLOv3 Keras

.

  MobileNet SSD v2 YOLOv3 Keras
Date of Release Jan 13, 2018
Model Type Object Detection Object Detection
Architecture
GitHub Stars 1900 7100

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.

How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix

YOLOv3 Keras

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. Keras implementation.

How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix
Learn more about MobileNet SSD v2
Learn more about YOLOv3 Keras

Compare MobileNet SSD v2 to other models

YOLOv3 Keras
YOLOv3 PyTorch
YOLOv4 PyTorch
YOLOv4 Darknet
YOLOv4 Tiny

Compare YOLOv3 Keras to other models

YOLOv8 Instance Segmentation
YOLOv8
YOLOv7 Instance Segmentation
OneFormer
MobileNet V2 Classification

Deploy a computer vision model today

Join 250,000 developers curating high quality datasets and deploying better models with Roboflow.

Get started