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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 โ€” from raw data to real-time predictions โ€” using EfficientNetV2S, a state-of-the-art deep learning [โ€ฆ]

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Amazing Trip to Slovakia โ€“ Hebrew

Amazing trip to Slovakia

ืžืกืœื•ืœ ื˜ื™ื•ืœ ื‘ืกืœื•ื‘ืงื™ื” ืœืžืฉืคื—ื” (9 ื™ืžื™ื): ื”ืจื™ ื”ื˜ื˜ืจื”, ืžืขืจื•ืช, ื˜ื™ืจื•ืช, ืจื›ื‘ืœื™ื ,ืื’ืžื™ื ื•ืคืกื’ื•ืช ืกืœื•ื‘ืงื™ื” ื›ืœืœื™ (ื—ืฉื•ื‘ ืžืื“ ืœืงืจื•ื) ื‘ื—ื™ืจืช ื”ืžืœื•ืŸ :ื”ืชืœื‘ื˜ื ื• ืœื’ื‘ื™ ืžื™ืงื•ื ื”ืžืœื•ืŸ ื•ื‘ื—ืจื ื• ื‘ืกื•ืคื• ืฉืœ ื“ื‘ืจ ืžืœื•ืŸ ื‘ื”ืจื™ ื”ื˜ื˜ืจื” ื”ื’ื‘ื•ื”ื™ื ืชื•ืš ื”ืชื—ืฉื‘ื•ืช ื‘ืงืจื™ื˜ืจื™ื•ื ื™ื ื”ื‘ืื™ื ืžื›ื™ื•ืŸ ืฉื‘ืžืœื•ื ื•ืช ื‘ืกืœื•ื‘ืงื™ื” ืื™ืŸ ืžื–ื’ืŸ . ื‘ื—ืจื ื• ื‘ื”ืจื™ ื”ื˜ื˜ืจื” ื”ื’ื‘ื•ื”ื™ื ืฉืฉื ืžืื“ ื ืขื™ื ื‘ื™ื•ื ื•ื‘ืœื™ืœื” ื—ื™ืคืฉื ื• ืžืœื•ืŸ ืฉืœื ื’ื•ื‘ื”

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How to Classify images using Efficientnet B0

How to Classify images using Efficientnet B0

Introduction In this tutorial, weโ€™ll explore how to use EfficientNetB0, a powerful deep learning model available in TensorFlow and Keras, for image classification. EfficientNet models are known for their efficiency and accuracy, making them an excellent choice for tasks like classifying objects in images. Weโ€™ll use a pre-trained EfficientNetB0 model trained on the ImageNet dataset,

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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. Weโ€™ll go step-by-step through: ๐Ÿ‘‰ย Watch the full tutorial here

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Face Swap ๐Ÿ˜Ž | Deep Fake | Swap Face in a Video with Your Own image using Roop

Deep fake

In this tutorial, weโ€™re diving into the world of Deepfake and face swapping using the Roop Python library. The goal of this video is to replace faces in a video with just one image, without the need for training or extensive datasets. Youโ€™ll be able to create face swap effects in no time The tutorial

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

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

๐ŸŽฃ Classify Fish Images Using MobileNetV2 & TensorFlow ๐Ÿง  In this hands-on video, Iโ€™ll show you how I built a deep learning model that can classify 9 different species of fish using MobileNetV2 and TensorFlow 2.10 โ€” all trained on a real Kaggle dataset! This Tensorflow image recognition tutorial covers from dataset splitting to live

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My Krakรณw Travel Guide: Best Places to Eat, Stay & Explore

krakow, town square, poland, city square, europe, tourism, old city, unesco heritage site, krakow, krakow, krakow, krakow, krakow, poland, poland, poland

Planning a trip to Krakรณw, Poland? check my Krakรณw Travel Guide This personal travel guide reveals the best places to eat, drink, and stay โ€” based on my experiences! From legendary Polish donuts and artisan pretzels to cozy cafรฉs and stylish boutique hotels, discover my local favorites around the Old Town. ๐Ÿฅจ Gorฤ…cy Precel Fโ€‘Wiatrak

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ืงืจืงื•ื‘ ื˜ื™ืคื™ื ื•ื”ืžืœืฆื•ืช โ€“ ืžื“ืจื™ืš ืœืžื˜ื™ื™ืœ ืœืงืจืงื•ื‘ : ืžืœื•ื ื•ืช , ืื˜ืจืงืฆื™ื•ืช , ืžืกืขื“ื•ืช ื•ืžืงื•ืžื•ืช ื˜ืขื™ืžื™ื

krakow, town square, poland, city square, europe, tourism, old city, unesco heritage site, krakow, krakow, krakow, krakow, krakow, poland, poland, poland

ืžื“ืจื™ืš ืงืจืงื•ื‘: ืื™ืคื” ืœืื›ื•ืœ, ืœื™ืฉื•ืŸ ื•ืœื‘ืงืจ โ€“ ื”ืžืคื” ื”ืžืœืื” ืœืžื˜ื™ื™ืœ ื‘ืจื•ื›ื™ื ื”ื‘ืื™ื ืœืžื“ืจื™ืš ืื˜ืจืงืฆื™ื•ืช ืงืจืงื•ื‘ ื‘ืขื‘ืจื™ืชโ€”ืกื™ื›ื•ื ืžืžื•ืงื“ ืฉืœ ื›ืœ ืžื” ืฉื›ื“ืื™ ืœื“ืขืช ืœืคื ื™ ื‘ื™ืงื•ืจ ื‘ืขื™ืจ ื”ื™ืคื” ื‘ืคื•ืœื™ืŸ. ื›ืืŸ ืชืžืฆืื• ืžืกืœื•ืœ ืจื’ืœื™ ื ื•ื— ื‘ืขื™ืจ ื”ืขืชื™ืงื”, ื ืงื•ื“ื•ืช ื—ื•ื‘ื” ื‘ืฉื›ื•ื ืช ืงื–โ€™ื™ืžื™ื™ื–โ€™, ื‘ื™ืงื•ืจ ื‘ืžื•ื–ื™ืื•ืŸ ืฉื™ื ื“ืœืจ ื•ื‘ืžื›ืจื•ืช ื”ืžืœื— ื‘ื•ื•ื™ื™ืœื™ืฆโ€™ืงื”, ื•ื’ื ืจืฉื™ืžืช ืžืกืขื“ื•ืช, ืžืืคื™ื•ืช ื•ื‘ืชื™ ืงืคื” ืฉืœื ืžืื›ื–ื‘ื™ื. ื”ื•ืกืคืชื™ ื”ืžืœืฆื•ืช ืœื™ื ื”

ืงืจืงื•ื‘ ื˜ื™ืคื™ื ื•ื”ืžืœืฆื•ืช โ€“ ืžื“ืจื™ืš ืœืžื˜ื™ื™ืœ ืœืงืจืงื•ื‘ : ืžืœื•ื ื•ืช , ืื˜ืจืงืฆื™ื•ืช , ืžืกืขื“ื•ืช ื•ืžืงื•ืžื•ืช ื˜ืขื™ืžื™ื Read More ยป

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Eran Feit