#efficientnet search results
#EfficientNet has achieved state of the art accuracy on #ImageNet while being 8.4x smaller and 6.1x faster!!
debuggercafe.com/brain-mri-clas… New post at DebuggerCafe - PyTorch EfficientNetB0 for Brain MRI Image Classification #PyTorch #EfficientNet #EfficientNetB0 #TransferLearning #FineTuning #ImageClassification #DeepLearning
Nice example of #UNet + #EfficientNet using @TensorFlow 2.2 and tf.keras:
UNet with EfficientNet encoder - @tensorflow 2.2.0 which shows using custom train and test step along keras fit colab.research.google.com/drive/1Tbyvr6J… @fchollet @random_forests
debuggercafe.com/transfer-learn… New tutorial at DebuggerCafe - Transfer Learning using EfficientNet PyTorch #PyTorch #DeepLearning #EfficientNet #EfficientNetB0 #TransferLearning #ImageClassification
Microsoft researchers training AI on chest X-rays: throughput is ~2000 images per second on IPU and ~166 images per second on GPU. Incredible performance gains for diagnostic imaging training on IPU! #EfficientNet #MedicalImaging #AI #IHINS @IntHealthAI @Azure
🎄Yeni blog yazısı: state-of-the-art modellerden #EfficientNet hakkında ve tabi ki örnek uygulamasıyla birlikte 😇 “Nasıl düşüneceğini bilmek, sadece ne düşüneceğini bilenlerin çok daha ötesinde olmanı sağlayacaktır.” Neil deGrasse Tyson link.medium.com/sbFzcyPzz2
debuggercafe.com/pytorch-pretra… New tutorial at DebuggerCafe - Image classification using pretrained PyTorch EfficientNetB0. Also compare inference time with that of ResNet50 on both CPU and GPU. #PyTorch #DeepLearning #EfficientNet #EfficientNetB0 #ImageClassification #ComputerVision
New post on DebuggerCafe. Train an EfficientNetB1 model on the Caltech UCSD Birds 200 dataset to recognize 200 species of birds. debuggercafe.com/caltech-ucsd-b… #PyTorch #ImageClassification #EfficientNet #NeuralNetworks #BirdClassification #AIforWildlife #ComputerVision #DeepLearning
How can I fine-tune EfficientNetB3 model and retain some of its exisiting labels? stackoverflow.com/questions/7166… #tensorflow #efficientnet #keras #transferlearning
RT How we made EfficientNet more efficient dlvr.it/S2Rh9R #efficientnet #convolutionneuralnet #modeltraining
Bird Box - websystemer.no/bird-box/ #deeplearning #editorspick #efficientnet #machinelearning #objectdetection
RT Accelerating Computer Vision: How we scaled EfficientNet to IPU-POD Supercomputing Systems dlvr.it/SFQYJj #convolutionneuralnet #efficientnet #machineintelligence
Unlock the secrets of image classification using Keras CV and EfficientNet! 📸 Learn to configure your Python environment, compile datasets, and apply advanced preprocessing and augmentation techniques. Read here 👉 folderit.net/image-classifi… #KerasCV #EfficientNet #FolderITBlog
ImageNetで1桁少ないパラメータサイズでSoTA。CPU推論で6倍高速化。乗るしかない、このビッグウェーブに Google AI Blog:EfficientNet: Improving Accuracy and Efficiency through AutoML and Model Scaling #TPU #EfficientNet ai.googleblog.com/2019/05/effici… @googleaiさんから
Our model garden is growing 🌹🌺🌻 Check out the @graphcoreai developer portal to access deployable machine learning applications for the IPU: hubs.la/H0YDgxd0 #BERT #ResNet #EfficientNet #MCMC #DeepVoice #Autoencoder #AI
Presenting a method for #olivedisease classification, based on an adaptive ensemble of two #EfficientNet-b0 models: “Efficient #DeepLearning Approach for Olive Disease Classification” by A. Bruno, D. Moroni, M. Martinelli. ACSIS Vol. 35 p. 889–894; tinyurl.com/4ssj8d8a
Olympic Sports Image Classification tutorial , with TensorFlow & EfficientNetV2 mages You can find link for the code in the blog : eranfeit.net/olympic-sports… Watch the full tutorial here : youtu.be/wQgGIsmGpwo Enjoy Eran #ImageClassification #Efficientnet #EfficientNetV2
Learning PyTorch by diving into EfficientNet’s architecture! Over 4 million parameters, but only 3.8K are trainable, showing how efficient it can be. Excited to keep exploring! #PyTorch #EfficientNet #DeepLearning #MachineLearning #GenerativeAI
Presenting a method for #olivedisease classification, based on an adaptive ensemble of two #EfficientNet-b0 models: “Efficient #DeepLearning Approach for Olive Disease Classification” by A. Bruno, D. Moroni, M. Martinelli. ACSIS Vol. 35 p. 889–894; tinyurl.com/4ssj8d8a
Rotate the ReLU to Sparsify Deep Networks Implicitly Nancy Nayak, Sheetal Kalyani tmlr.infinite-conf.org/paper_pages/Nz… #efficientnet #regularizer #regularization
Unlock the secrets of image classification using Keras CV and EfficientNet! 📸 Learn to configure your Python environment, compile datasets, and apply advanced preprocessing and augmentation techniques. Read here 👉 folderit.net/image-classifi… #KerasCV #EfficientNet #FolderITBlog
#EfficientNet has achieved state of the art accuracy on #ImageNet while being 8.4x smaller and 6.1x faster!!
debuggercafe.com/brain-mri-clas… New post at DebuggerCafe - PyTorch EfficientNetB0 for Brain MRI Image Classification #PyTorch #EfficientNet #EfficientNetB0 #TransferLearning #FineTuning #ImageClassification #DeepLearning
Microsoft researchers training AI on chest X-rays: throughput is ~2000 images per second on IPU and ~166 images per second on GPU. Incredible performance gains for diagnostic imaging training on IPU! #EfficientNet #MedicalImaging #AI #IHINS @IntHealthAI @Azure
300M unlabelled images vs 3.5B labelled images. The FSD industry has been dying for something like this. The weekend warrior engineers thank you, Google. @hardmaru @JeffDean #NoisyStudent #EfficientNet
Nice example of #UNet + #EfficientNet using @TensorFlow 2.2 and tf.keras:
UNet with EfficientNet encoder - @tensorflow 2.2.0 which shows using custom train and test step along keras fit colab.research.google.com/drive/1Tbyvr6J… @fchollet @random_forests
debuggercafe.com/transfer-learn… New tutorial at DebuggerCafe - Transfer Learning using EfficientNet PyTorch #PyTorch #DeepLearning #EfficientNet #EfficientNetB0 #TransferLearning #ImageClassification
Bird Box - websystemer.no/bird-box/ #deeplearning #editorspick #efficientnet #machinelearning #objectdetection
How can I fine-tune EfficientNetB3 model and retain some of its exisiting labels? stackoverflow.com/questions/7166… #tensorflow #efficientnet #keras #transferlearning
Unlock the secrets of image classification using Keras CV and EfficientNet! 📸 Learn to configure your Python environment, compile datasets, and apply advanced preprocessing and augmentation techniques. Read here 👉 folderit.net/image-classifi… #KerasCV #EfficientNet #FolderITBlog
This is my notebook w/ a simple #KNN experiment on this. kaggle.com/code/moeinshar… You can see the results of different methods on simple KNN classification on CIFAR10 w/ pre-trained #efficientnet here. Embedding size: 1280D --> 64D, w/o any extra training!
📢 Read our recent publication 📚 #Rock #ImageClassification Based on #EfficientNet and #TripletAttention Mechanism 🔗 doi.org/10.3390/app130… 👨🔬 by Mr. Zhihao Huang et al. #SpecialIssue 🔗 mdpi.com/topics/Machine… #OpenAccess #mdpiapplsci
New post on DebuggerCafe. Train an EfficientNetB1 model on the Caltech UCSD Birds 200 dataset to recognize 200 species of birds. debuggercafe.com/caltech-ucsd-b… #PyTorch #ImageClassification #EfficientNet #NeuralNetworks #BirdClassification #AIforWildlife #ComputerVision #DeepLearning
Our model garden is growing 🌹🌺🌻 Check out the @graphcoreai developer portal to access deployable machine learning applications for the IPU: hubs.la/H0YDgxd0 #BERT #ResNet #EfficientNet #MCMC #DeepVoice #Autoencoder #AI
debuggercafe.com/pytorch-pretra… New tutorial at DebuggerCafe - Image classification using pretrained PyTorch EfficientNetB0. Also compare inference time with that of ResNet50 on both CPU and GPU. #PyTorch #DeepLearning #EfficientNet #EfficientNetB0 #ImageClassification #ComputerVision
📢 #HighlyViewedPapers 📚 Rock Image Classification Based on EfficientNet and Triplet Attention Mechanism 🔗 mdpi.com/2076-3417/13/5… 👨🔬 by Mr. Zhihao Huang et al. #rockimage #EfficientNet #imageclassification
Presenting a method for #olivedisease classification, based on an adaptive ensemble of two #EfficientNet-b0 models: “Efficient #DeepLearning Approach for Olive Disease Classification” by A. Bruno, D. Moroni, M. Martinelli. ACSIS Vol. 35 p. 889–894; tinyurl.com/4ssj8d8a
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