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Image Classification

Olympic Sports Image Classification with EfficientNetV2

Efficientnet olympic build model custom dataset

Introduction Image classification is one of the most exciting applications of computer vision. It powers technologies in sports analytics, autonomous driving, healthcare diagnostics, and more. In this project, we take you through a complete, end-to-end workflow for classifying Olympic sports images — from raw data to real-time predictions — using EfficientNetV2S, a state-of-the-art deep learning […]

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How To Actually Use MobileNetV3 for Fish Classifier

MobileNetV3 classify images transfer learning

This is a transfer learning tutorial for image classification using TensorFlow involves leveraging pre-trained model MobileNet-V3 to enhance the accuracy of image classification tasks. By employing transfer learning with MobileNet-V3 in TensorFlow, image classification models can achieve improved performance with reduced training time and computational resources. We’ll go step-by-step through: 👉 Watch the full tutorial here

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How To Actually Fine-Tune MobileNetV2 | Classify 9 Fish Species

How To Actually Fine-Tune MobileNetV2 | Classify 9 Fish Species

🎣 Classify Fish Images Using MobileNetV2 & TensorFlow 🧠 In this hands-on video, I’ll show you how I built a deep learning model that can classify 9 different species of fish using MobileNetV2 and TensorFlow 2.10 — all trained on a real Kaggle dataset! From dataset splitting to live predictions with OpenCV, this tutorial covers

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Self-Supervised Learning Made Easy with LightlyTrain | Image Classification tutorial

LightlyTrain Image classification

In this tutorial, we will show you how to use LightlyTrain to train a model on your own dataset for image classification. Self-Supervised Learning (SSL) is reshaping computer vision, just like LLMs reshaped text. The newly launched LightlyTrain framework empowers AI teams—no PhD required—to easily train robust, unbiased foundation models on their own datasets. Let’s

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Object Classification using XGBoost and VGG16 | Classify vehicles using Tensorflow

vehichles XGBOOST

In this tutorial, we build a vehicle classification model using VGG16 for feature extraction and XGBoost for classification! 🚗🚛🏍️ It will based on Tensorflow and Keras 🔍 What You’ll Learn 🔍:  🖼️ Part 1: We kick off by preparing our dataset, which consists of thousands of vehicle images across five categories. We demonstrate how to

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How to classify Malaria Cells using Convolutional neural network

CNN Malaria

This tutorial provides a step-by-step easy guide on how to implement and train a CNN model for Malaria cell classification using TensorFlow and Keras. 🔍 What You’ll Learn 🔍:  Data Preparation — In this part, you’ll download the dataset and prepare the data for training. This involves tasks like preparing the data , splitting into training

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Build a CNN Model for Retinal Image Diagnosis

Tensorflow retinal eye

👁️ CNN Image Classification for Retinal Health Diagnosis with TensorFlow and Keras! 👁️ How to gather and preprocess a dataset of over 80,000 retinal images, design a CNN deep learning model , and train it that can accurately distinguish between these health categories. What You’ll Learn: 🔹 Data Collection and Preprocessing: Discover how to acquire

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120 Dog Breeds, more than 10,000 Images: Deep Learning Tutorial for dogs classification

Tensorflow 120 dog breeds

📽️ In our latest video tutorial, we will create a dog breed recognition model using the NasLarge pre-trained model 🚀 and a massive dataset featuring over 10,000 images of 120 unique dog breeds 📸. What You’ll Learn: 🔹 Data Preparation: We’ll begin by downloading a dataset of of more than 20K Dogs images, neatly categorized

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🦕Dinosaur Image Classification Tutorial using Convolutional Neural Network

Tensorflow dinosaor

Welcome to our comprehensive Dinosaur Image Classification Tutorial! We’ll learn how use Convolutional Neural Network (CNN) to classify 5 dinosaur categories , based on 200 images : You can find more tutorials, and join my newsletter here : https://eranfeit.net/ If you are interested in learning modern Computer Vision course with deep dive with TensorFlow ,

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