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Efficientnet 61 Planet Detection

Developed by chlab
EfficientNetV2 is a highly efficient convolutional neural network architecture, specially optimized for training speed and parameter efficiency. The 61-channel version is a variant of this architecture.
Downloads 14
Release Time : 6/16/2022

Model Overview

EfficientNetV2 is a series of image classification models developed by Google, achieving a balance between accuracy and efficiency through compound scaling methods. The 61-channel version is a specific configuration of this series.

Model Features

Efficient Architecture
Uses compound scaling methods to optimize model depth, width, and resolution, achieving better parameter efficiency.
Fast Training
Compared to the previous generation EfficientNet, the V2 version significantly improves training speed.
61-channel Configuration
A variant version with a specific number of channels, possibly optimized for performance in specific scenarios.

Model Capabilities

Image Classification
Visual Feature Extraction

Use Cases

Computer Vision
Object Recognition
Identify object categories in images
Performs well on benchmark datasets like ImageNet
Image Classification
Classify image content
Supports classification of multiple common object categories
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