Product
Solutions
Resources
Pricing
Docs
Talk to SalesSign in
Models
YOLOX vs. MobileNet V2 Classification

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

YOLOX vs. MobileNet V2 Classification

Both

YOLOX

and

MobileNet V2 Classification

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

YOLOX

and

MobileNet V2 Classification

.

  YOLOX MobileNet V2 Classification
Date of Release Jul 18, 2021
Model Type Object Detection Classification
Architecture CNN, YOLO
GitHub Stars 7600

YOLOX

YOLOX is a high-performance object detection model.

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

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 AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix
Learn more about YOLOX
Learn more about MobileNet V2 Classification

Compare YOLOX to other models

MobileNet V2 Classification
MobileNet SSD v2
YOLOv3 Keras
YOLOv3 PyTorch
YOLOv4 PyTorch

Compare MobileNet V2 Classification to other models

YOLOv8 Instance Segmentation
YOLOv8
YOLOv7 Instance Segmentation
OneFormer
YOLOv3 Keras

Deploy a computer vision model today

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

Get started