Eran Feit

Eran Feit is a Computer Vision Engineer, AI Researcher, and Deep Learning Educator with over a decade of hands-on experience in the tech industry. Specializing in object detection, edge AI deployment, and advanced neural network architectures, Eran bridges the gap between complex AI theory and practical implementation. He is dedicated to empowering the global developer community through comprehensive, code-driven tutorials and guides.

TensorFlow Image Classification Tutorial: Flower Recognition with Keras

TensorFlow tutorials /
TensorFlow Image Classification

TensorFlow Image Classification with Keras: Flower Recognition, Data Augmentation, and OpenCV Prediction In this comprehensive TensorFlow Image Classification Tutorial, we will explore how to build and deploy a robust deep learning model to recognize various flower species using Python. Image classification is a fundamental pillar of Computer Vision, and by leveraging the Keras API within […]

TensorFlow Image Classification Tutorial: Flower Recognition with Keras Read More »

How to classify images using MobileNet Tensorflow and ResNet50

TensorFlow tutorials /
TensorFlow Image Classification Tutorial: ResNet50 vs. MobileNet

TensorFlow MobileNetV2 vs ResNet50: Image Classification with Pretrained Models ResNet50 vs MobileNetV2 Deep learning offers a wide range of pre‑trained architectures for image classification. ResNet50 is part of the Residual Networks family introduced in 2015. It addresses the degradation problem encountered when training very deep networks by using residual blocks with skip connections, which allow information

How to classify images using MobileNet Tensorflow and ResNet50 Read More »

How To Build Sports Image Classification Model Using MobileNet

TensorFlow tutorials /
sports image classification

Why Use Convolutional Neural Networks (CNN) for Custom Sports Image Classification? In the rapidly evolving world of sports analytics, the ability to automatically identify athletic disciplines in visual data is a game-changer. This tutorial provides a comprehensive guide to build a custom sports image classifier with TensorFlow and Keras. Whether you are automating highlights or

How To Build Sports Image Classification Model Using MobileNet Read More »

TensorFlow Food Image Classification: 36 Fruits and Vegetables in Python (Keras + OpenCV)

TensorFlow tutorials /
food classification

Build a Food Classification Pipeline with Python and TensorFlow Introduction TensorFlow food image classification is a practical way to recognize what’s inside an image and turn pixels into a label your app can use.In this tutorial, you’ll build a 36-class fruits and vegetables classifier in Python using TensorFlow / Keras, while using OpenCV for consistent

TensorFlow Food Image Classification: 36 Fruits and Vegetables in Python (Keras + OpenCV) Read More »

PixelLib Mask R-CNN Tutorial: Custom Training with LabelMe + TensorFlow

TensorFlow tutorials, Object Detection /
PixelLib

What is PixelLib for Instance Segmentation? Are you struggling to build a precise instance segmentation pipeline without dealing with hundreds of lines of complex boilerplate code? In this hands-on guide, you will master PixelLib Mask R-CNN custom training with LabelMe to detect, segment, and extract specific objects in your images. Whether you are building an

PixelLib Mask R-CNN Tutorial: Custom Training with LabelMe + TensorFlow Read More »

Eran Feit