![]() ![]() AlexNet has definitely found cult status in the ImageNet challenge (ILSVRC) competition history. Prior to 2012, the image classification model error rate was around 25% but AlexNet shockingly surpassed that error rate with 15.3 in the 2012 ImageNet challenge.ĪlexNet is often regarded as the pioneer of the convolutional neural network and starting point of the Deep Learning boom. AlexNet | ILSVRC Competition – 2012 (Winner) | Top-5 Error Rate – 15.3%ĪlexNet was a Convolutional Neural Network designed by Alex Krizhevsky’s team that leveraged GPU training for better efficiency. We’ll also see what all advantages they provide and where they need to improve. In this section, we’ll go through the deep learning models that won in the Imagenet Challenge ILSVRC competition history. Popular Deep Learning Models of ImageNet Challenge (ILSVRC) Competition History It was an outstanding step by her considering other researchers were trying to improve ML algorithms, Fei-Fei Li decided to improve the dataset for better training of ML models and launched the database in 2009. ImageNet Fei-Fei Li ( Source)Īnnoyed with the issues of lack of quality image dataset for training ML models and inspired by the WordNet hierarchy, Fei-Fei Li along with her team members started a project known as ImageNet that was aimed to build an improved dataset of images. In those days, she was working in the field of medical imaging and faced issues in designing machine learning models due to a lack of quality images. The idea of the ImageNet visual database was conceived by Fei-Fei Li, a Professor of Computer Science at Stanford University in 2006. ImageNet Dataset is of high quality and that’s one of the reasons it is highly popular among researchers to test their image classification model on this dataset. ImageNet is a visual Dataset that contains more than 15 million of labeled high-resolution images covering almost 22,000 categories. What is ImageNet ? ImageNet Visual Dataset ( Source) In this article, we will take a look at the popular deep learning models of ImageNet challenge competition history also known as ImageNet Large Scale Visual Recognition Challenge or ILSVRC. Of course, researchers played an important role in the emergence of deep learning, but the story cannot be complete without the ImageNet visual database and its annual contest with more than millions of labeled images that helped the researcher to train and benchmark their models. ![]() ![]() ![]() Nowadays the error rate of these image classification models hover around 3%, but a decade back the error rates of the best models were around 25%. Image Classification is now considered a fairly solved problem thanks to state-of-art deep learning models. 6.1 Human Beings | Top-5 Error Rate – 5.1%.PNASNet-5 | ILSVRC Competition – 2018 (Winner) | Top-5 Error Rate – 3.8% ResNeXt-10 | ILSVRC Competition – 2016 (Runners Up) | Top-5 Error Rate – 4.1% ResNet | ILSVRC Competition – 2015 (Winner) | Top-5 Error Rate – 3.57% VGG-16 | ILSVRC Competition – 2014 (Runners-Up) | Top-5 Error Rate – 7.3% Inception V1 (GoogLeNet) | ILSVRC Competition – 2014 (Winner) | Top-5 Error Rate – 6.67% ZFNet | ILSVRC Competition – 2013 (Winner) | Top-5 Error Rate – 11.2% AlexNet | ILSVRC Competition – 2012 (Winner) | Top-5 Error Rate – 15.3% 5 Popular Deep Learning Models of ImageNet Challenge (ILSVRC) Competition History.4 What is ImageNet Large Scale Visual Recognition Challenge (ILSVRC). ![]()
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