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
#ConvolutionalNeuralNetworks (#CNNs in short) are immensely useful for many #imageProcessing tasks and much more...
Yet you sometimes encounter some bits of code with little explanation. Have you ever wondered about the origins of the values for image normalization in #imagenet ?
[0.485, 0.456, 0.406] (for R, G and B channels respectively)[0.229, 0.224, 0.225]Strangest to me is the need for a three-digits precision. Here, after finding the origin of these numbers for MNIST and ImageNet, I am testing if that precision is really important : guess what, it is not (so much) !
👉 if interested in more details, check-out https://laurentperrinet.github.io/sciblog/posts/2024-12-09-normalizing-images-in-convolutional-neural-networks.html
📽️ 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 📸.
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
🚨 Blogpost alert | Our newest blog entry delves into the use of #MachineLearning in #ClimateModelling. In the blogpost, we point out the most interesting aspects of the study “Identifying climate models based on their daily output using machine learning”, by researchers Lukas Brunnel and Sebastian Sippel. 🔎 This research sheds light on how #ConvolutionalNeuralNetworks can be trained to identify #ClimateModels using daily temperature maps. 🌡️
👀 Read the article here: https://buff.ly/3S7vzJf
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
Welcome to artificial intelligence and weather image prediction tutorial !
In this tutorial, we dive deep into Convolutional Neural Networks (CNNs) using TensorFlow and Keras to categorize weather patterns.
The link for the video tutorial is here : https://youtu.be/gFiISJPCpKs
Enjoy
Eran
#Python #Cnn #TensorFlow #Deeplearning #TensorFlowweatherprediction #KerasCNNtutorial #ConvolutionalNeuralNetworks #Weatherimageclassification #Deeplearningweather
🚀 In this video tutorial, we will demonstrate visual style transfer AI and creativity between images 🎨
Learn how to use Neural Style Transfer with Python and TensorFlow, and merge the content of one image with the artistic style of another.
The link for the tutorial : https://youtu.be/ewvjICAaoX4
Enjoy
Eran
#python #neuralstyletransfer #TensorFlowtutorial #PythonAIart #imagesynthesis #artisticimagetransfer #convolutionalneuralnetworks #deeplearningcreativity #AIimagestyling
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) 📊 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
📣 Congratulations are in order for Rikiya Yamashita et al., as their article that looks at #ConvolutionalNeuralNetworks and its application to radiological tasks is once again the Most Downloaded #InsightsIntoImaging article of the month (June 2023)!
Well done!
🔗 https://insightsimaging.springeropen.com/articles/10.1007/s13244-018-0639-9
I experimented with using Large Language Models to solve a complex #imagerecognition problem.
The generated machine learning model by ChatGPT using a few prompts was able to detect #MNIST handwritten digits with an accuracy of 98%.
Read on if you want to learn how I did this.
#AI #artificialintelligence #deeplearning #neuralnetworks #bingai #bingchat #convolutionalneuralnetworks #LLMs #computervision
"Emergence of brain-like mirror-symmetric viewpoint tuning in convolutional neural networks"
https://www.biorxiv.org/content/10.1101/2023.01.05.522909v1
#Neuroscience #Neuro #ComputationalNeuroscience #Vision #MachineLearning #DeepLearning #ConvolutionalNeuralNetworks
Neelesh Rampal from NIWA teaches us the difference between #linearregression and #convolutionalneuralnetworks #AMOS2022
Abseits dieser Ausstellung gibt es ein (offenbar noch nicht dokumentiertes) interaktives Exponat eines #ConvolutionalNeuralNetworks zur #Bilderkennung, bei dem alle Zwischenergebnisse der Convolutional, Pool und Fully-Connected-Layer auf eigenen Monitoren dargestellt sind. Mit einer Kamera kann man beliebige (vorhandene) Objekte und Bild-Karten aufnehmen und sich das Klassifikationsergebnis inklusive Konfidenz ansehen. Sehr interessant.
