TruongNV-hut/AIcandy_MobileNet_ImageClassification_gargdlos
MobileNet for Image Classification
This project helps developers build image classification systems for resource-constrained devices like mobile phones or embedded systems. You provide a dataset of images with labels, and it outputs a trained model capable of identifying categories in new images efficiently. This is for software developers and AI engineers who need to deploy computer vision solutions on devices with limited computational power.
No commits in the last 6 months.
Use this if you need to classify images on mobile or embedded devices where computational efficiency and small model size are critical.
Not ideal if you are working with high-performance computing environments and can leverage larger, more complex models for potentially higher accuracy.
Stars
28
Forks
2
Language
Python
License
—
Category
Last pushed
Sep 18, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/TruongNV-hut/AIcandy_MobileNet_ImageClassification_gargdlos"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
qubvel/efficientnet
Implementation of EfficientNet model. Keras and TensorFlow Keras.
KichangKim/DeepDanbooru
AI based multi-label girl image classification system, implemented by using TensorFlow.
matlab-deep-learning/Image-Classification-in-MATLAB-Using-TensorFlow
This example shows how to call a TensorFlow model from MATLAB using co-execution with Python.
harvitronix/five-video-classification-methods
Code that accompanies my blog post outlining five video classification methods in Keras and TensorFlow
AFAgarap/cnn-svm
An Architecture Combining Convolutional Neural Network (CNN) and Linear Support Vector Machine...