Super-Quick Image Classification with MobileNetV2

You can find link for the code in the blog : https://eranfeit.net/super-quick-image-classification-with-mobilenetv2/

Check out our tutorial : https://youtu.be/Nhe7WrkXnpM&list=UULFTiWJJhaH6BviSWKLJUM9sg

Enjoy
Eran

#Python #ImageClassification #MobileNetV2

Super-Quick Image Classification with MobileNetV2 - Eran Feit

How to classify images using MobileNet V2 ? Want to turn any JPG into a set of top-5 predictions in under 5 minutes? In this hands-on tutorial I’ll walk you line-by-line through loading MobileNetV2, prepping an image with OpenCV, and decoding the resultsβ€”all in pure Python. Perfect for beginners who need a lightweight model or

Eran Feit -

🎯 AI isn’t just about textβ€”image classification is driving major innovations across industries!

Learn how businesses are using this tech to improve healthcare diagnostics, boost retail efficiency, and more.

πŸ”— Read the blog: https://www.softwebsolutions.com/resources/key-use-cases-and-best-practices-of-image-classification-services.html

#AI #ImageClassification #DeepLearning #ComputerVision #TechForGood

What are the top trends and best practices for image classification in 2025?

Explore the top applications, real-world use cases, and best practices of AI-powered image classification in 2025. Discover transforming industries with intelligent visual analysis.

Softweb Solutions

In this tutorial, we will show you how to use Self-Supervised Learning LightlyTrain to train a model on your own dataset for image classification.

more info : https://www.lightly.ai/lightlytrain?utm_source=youtube&utm_medium=description&utm_campaign=eran

Tutorial : https://youtu.be/MHXx2HY29uc

Enjoy
Eran

#Python #ImageClassification #LightlyTrain

Lightly Train

LightlyTrain empowers you to create robust models faster through self-supervised learning. Pre-train models self-supervised and generate meaningful embeddings.

How to classify Malaria Cells using Convolutional neural network

You can find link for the code in the blog : https://eranfeit.net/how-to-classify-malaria-cells-using-convolutional-neural-network/

Check out our tutorial here : https://youtu.be/WlPuW3GGpQo&list=UULFTiWJJhaH6BviSWKLJUM9sg

Enjoy
Eran

#Python #imageclassification #convolutionalneuralnetworks #transferlearning

How to classify Malaria Cells using Convolutional neural network – Eran Feit

🎯 Empower Your AI with High-Quality Image Classification Datasets! πŸ–ΌοΈπŸ€–

Unlock the potential of your machine learning models with GTS AI's image classification dataset services. Whether it’s object recognition, scene analysis, or medical imaging, our datasets are tailored to drive accuracy and performance.

Take your AI projects to the next level with data you can trust. Explore more here: https://gts.ai/services/image-classification-services/

#ImageClassification #AIData #MachineLearning #ComputerVision #GTS_AI

Image Classification Services

Discover advanced Image Classification Services. Transform your images into actionable insights using state-of-the-art algorithms.

πŸ“½οΈ In our latest video tutorial, we will create a dog breed recognition model using the NasLarge pre-trained model πŸš€ and a massive dataset featuring over 10,000 images of 120 unique dog breeds πŸ“Έ.

Check out our tutorial here : https://youtu.be/vH1UVKwIhLo&list=UULFTiWJJhaH6BviSWKLJUM9sg

You can find link for the code in the blog : https://eranfeit.net/120-dog-breeds-more-than-10000-images-deep-learning-tutorial-for-dogs-classification/

Enjoy
Eran

#Python #Cnn #TensorFlow #deeplearning #neuralnetworks #imageclassification #convolutionalneuralnetworks #computervision #transferlearning

120 Dog Breeds, more than 10,000 Images: Deep Learning Tutorial for dogs classification πŸ•β€πŸ¦Ί

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Three deep-learning tools, referred to collectively as CHiMP, were created for analysis of micrographs of protein crystallization experiments at the DLS synchrotron, UK. #Crystallization #ImageClassification #ObjectDetection https://doi.org/10.1107/S2059798324009276
CHiMP: deep-learning tools trained on protein crystallization micrographs to enable automation of experiments

A description is given of new deep-learning tools that analyse experimental micrographs of crystallization experiments to enable the automation of outcome classification, crystal detection and determination of locations to dispense compounds for fragment-based drug discovery at Diamond Light Source.

Acta Crystallographica Section D

Discover how to build a CNN model for skin melanoma classification using over 20,000 images of skin lesions

Check out our tutorial here : https://youtu.be/RDgDVdLrmcs

Enjoy
Eran

#Python #Cnn #TensorFlow #deeplearning #neuralnetworks #imageclassification #convolutionalneuralnetworks #SkinMelanoma #melonomaclassification

Skin Melanoma Classification using CNN | Step-by-Step Guide with 20,000+ Images

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The review of a PhD thesis on Abstract Concept Image Classification motivated me to do a few small experiments with Midjourney. I simply provided the title of an abstract concept, as e.g. "safety", as a prompt, nothing else, and this is what Midjourney "understands" under "safety" ;-)

#generativeAI #AI #AIart #imageclassification @fizise

Hi,

🌼 In our latest video tutorial, we will dive into image classification using Python and TensorFlow.
Discover how to create a Convolutional Neural Network (CNN) πŸ“Š that can identify various types of flowers 🌻.

The link for the video tutorial is here : https://youtu.be/AamKeCTRSKM

Enjoy

Eran

#Python #Cnn #TensorFlow #Deeplearning #convolutionalneuralnetworks #imageClassification

TensorFlow CNN Tutorial: Flower Classification with Python

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