How to Classify images using Efficientnet B0
Classify any image in seconds using Python and the pre-trained EfficientNetB0 model from TensorFlow.This beginner-friendly tutorial shows how to load an
Classify any image in seconds using Python , EfficientNetB0 model and TensorFlow.
You can find link for the code in the blog : eranfeit.net/how-to-class...
Link for the tutorial : youtu.be/lomMTiG9UZ4
Enjoy
Eran
#Python #ImageClassification #Efficientnet #tensorflow #EfficientnetB0
01.08.2025 05:37 β π 0 π 0 π¬ 0 π 0
Transfer learning tutorial for image classification using MobileNet-V3 .
You can find link for the code in the blog : eranfeit.net/how-to-actua...
Watch the full tutorial here: youtu.be/12GvOHNc5DI
Enjoy
Eran
#Python #ImageClassification
05.07.2025 14:21 β π 0 π 0 π¬ 0 π 0
How To Actually Fine-Tune MobileNetV2 | Classify 9 Fish Species
π£ Classify Fish Images Using MobileNetV2 & TensorFlow π§ In this hands-on video, Iβll show you how I built a deep learning model that can classify 9
π£ Classify Fish Images Using MobileNetV2 & TensorFlow π§
In this video, we will learn to classify 9 different species of fish using MobileNetV2 and TensorFlow
Link for the code : eranfeit.net/how-to-actua...
full tutorial here: youtu.be/9FMVlhOGDoo
Enjoy
Eran
20.06.2025 13:37 β π 0 π 0 π¬ 0 π 0
How to Improve Image and Video Quality ?
Check out our tutorial here : youtu.be/sjhZjsvfN_o&...
You can find more tutorials, and join my newsletter here : eranfeit.net/blog
Enjoy
Eran
#OpenCV #computervision #superresolution #SColorizingSGrayImages #ColorizingOldImages
06.06.2025 05:51 β π 1 π 0 π¬ 0 π 0
Super-Quick Image Classification with MobileNetV2
Want to turn any image into top-5 predictions in under 5 minutes?
You can find link for the code in the blog : eranfeit.net/super-quick-...
Check out our tutorial : youtu.be/Nhe7WrkXnpM&...
Enjoy
Eran
#Python #ImageClassification #MobileNetV2
21.05.2025 16:04 β π 0 π 0 π¬ 0 π 0
Amazing Color Transfer between Images
Learn how to transform the colors of one image to mimic those of another.
You can find more tutorials, and join my newsletter here : eranfeit.net/blog
Check out our tutorial here : youtu.be/n4_qxl4E_w4&...
Enjoy
Eran
#OpenCV #colortransfer
01.05.2025 09:49 β π 0 π 0 π¬ 0 π 0
Lightly Train
LightlyTrain empowers you to create robust models faster through self-supervised learning. Pre-train models self-supervised and generate meaningful embeddings.
In this tutorial, we will show you how to use LightlyTrain
Self-Supervised Learning (SSL) is reshaping computer vision, just like LLMs reshaped text.
LightlyTrain page: www.lightly.ai/lightlytrain...
Check out our tutorial here : youtu.be/MHXx2HY29uc&...
Enjoy
Eran
15.04.2025 13:06 β π 1 π 0 π¬ 0 π 0
Image animation brings life to the static face in the source image according to the driving video, using the Thin-Plate Spline Motion Model!
You can find more tutorials, and join my newsletter here : eranfeit.net
Check out our tutorial here : youtu.be/oXDm6JB9xak&...
Enjoy
Eran
11.04.2025 20:08 β π 0 π 0 π¬ 0 π 0
Code for Object Classification using XGBoost and VGG16 | Classify vehicles using Tensorflow - Eran Feit's Ko-fi Shop
Link for the tutorial : https://youtu.be/WlPuW3GGpQo&list=UULFTiWJJhaH6BviSWKLJUM9sg
In this tutorial, we build a vehicle classification model using ...
In this tutorial, we build a vehicle classification model using VGG16 for feature extraction and XGBoost for classification! ππποΈ
You can find link for the code in the blog : ko-fi.com/s/9bc3ded198
Check out our tutorial here : youtu.be/taJOpKa63RU&...
Enjoy
Eran
29.03.2025 14:35 β π 0 π 0 π¬ 0 π 0
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.
You can find link for the code in the blog : eranfeit.net/how-to-class...
01.03.2025 11:38 β π 0 π 0 π¬ 0 π 0
How to segment X-Ray lungs using U-Net and Tensorflow β Eran Feit
This tutorial provides a step-by-step guide on how to implement and train a U-Net model for X-Ray lungs segmentation using TensorFlow/Keras.
You can find link for the code in the blog :
eranfeit.net/how-to-segme...
Enjoy
Eran
17.02.2025 15:09 β π 0 π 0 π¬ 0 π 0
Medical Melanoma Detection | TensorFlow U-Net Tutorial usingΒ Unet β Eran Feit
Medical Melanoma Detection
This tutorial provides how to implement and train a U-Net model for Melanoma detection.
You can find link for the code in the blog : eranfeit.net/medical-mela...
Enjoy
Eran
#Python #openCV #TensorFlow #Deeplearning #ImageSegmentation #Unet #Resunet
24.01.2025 11:57 β π 0 π 0 π¬ 0 π 0
How to implement and train a U-Net model for persons segmentation using TensorFlow/Keras.
The tutorial is divided into four parts:
You can find link for the code in the blog : eranfeit.net/u-net-image-...
Check out our tutorial here : youtu.be/ZiGMTFle7bw&...
Enjoy
Eran
14.01.2025 19:20 β π 1 π 0 π¬ 0 π 0
This tutorial provides a step-by-step guide on how to implement and train a U-Net model for polyp segmentation using TensorFlow/Keras.
You can find link for the code in the blog : eranfeit.net/u-net-medica...
Check out our tutorial here : youtu.be/YmWHTuefiws&...
Enjoy
Eran
20.12.2024 17:56 β π 0 π 0 π¬ 0 π 0
Learn CNN Image Classification for Retinal Health Diagnosis with TensorFlow and Keras! ποΈ
You can find link for the code in the blog : eranfeit.net/build-a-cnn-...
Check out our tutorial here : youtu.be/PVKI_fXNS1E&...
Enjoy
Eran
07.12.2024 17:26 β π 1 π 0 π¬ 0 π 0
Lead by Prof. @thomasbrox.bsky.social
https://lmb.informatik.uni-freiburg.de/
Cognitive Computer Vision Lab @UniFAU.bsky.social
empowered by Andreea Dogaru, Shreya Kapoor, Maximilian Weiherer
led by @VisionBernie.bsky.social
Computer Vision Laboratory @ Kyoto University (Ko Nishino, Ken Sakurada, Ryo Kawahara)
https://vision.ist.i.kyoto-u.ac.jp/
Computer Vision and Learning research group @ LMU Munich, headed by BjΓΆrn Ommer.
Generative Vision (Stable Diffusion, VQGAN) & Representation Learning
π https://ommer-lab.com
Official Account for the European Conference on Computer Vision (ECCV) #ECCV2026, Malmo πΈπͺ Hosted by @jbhaurum and @CSProfKGD
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Bugs, feature requests, feedback: support@bsky.app