ResNet34 with tinyImageNet.ipynb Shows the training process and results of ResNet-34 et SE-Resnet-34 models on Tiny ImageNet with and without data augmentation. ![]() ResNet18 with tinyImageNet.ipynb Shows the training process and results of ResNet-18 et SE-Resnet-18 models on Tiny ImageNet with and without data augmentation.InceptionV3 with CIFAR10-100.ipynb Shows the training process and results of InceptionV3 et SE-InceptionV3 models on CIFAR-100.ResNeXt with CIFAR100.ipynb Shows the training process and results of ResNeXt et SE-ResneXt models on CIFAR-100.ResNet with CIFAR100.ipynb Shows the training process and results of ResNet et SE-Resnet models on CIFAR-100.InceptionV3 with CIFAR10-100.ipynb Shows the training process and results of InceptionV3 et SE-InceptionV3 models on CIFAR-10.ResNeXt with CIFAR10.ipynb Shows the training process and results of ResNeXt et SE-ResneXt models on CIFAR-10.ResNet with CIFAR10.ipynb Shows the training process and results of ResNet et SE-Resnet models on CIFAR-10.Load and Test Models.ipynb loads all the saved models and computes the top-1,3 and 5 accuracy on the associated test data sets.Models are ordered by test category folders (link below) We also tried to analyze the effect of different parameters of Squeeze-and-Excitation blocks on the models, matching the paper’s findings with varying success. Because of technical barriers, slightly different models and data sets were used. This paper is going to show how we were able to increase the accuracy of CNN models with the Squeeze-and-Excitation method. The original paper showed that it consistently increased the classification accuracy with various data sets such as Image Net. This report investigates the effectiveness of Squeeze-and-Excitation blocks whose aim is to strengthen the inter-channel relationship by rescaling them. Convolutional neural networks are widely used for image classification in models such as Resnet models. To sum up, Squeed packs elementary metadata editing capabilities and allows you to customize the tracks naming or numbering pattern, and so on.Īt the same time, Squeed also integrates more complex capabilities: it can go online to search for exhaustive metadata details and cover art, or can convert the associated information into tags.This report summarizes the findings of the original Squeeze-and-Excitation Networks paper and shows a reproduction of the results with Tensorflow. User-friendly metadata editor that comes with a streamlined workflow The utility offers you the option to import the data to your own tracks with a simple mouse click. What’s more, Squeed can go online and search for metadata information in the Discogs user created database. Squeed allows you to define custom renaming patterns, can automatically number tracks based on your indications, and enables you to extract metadata information and use it to create tags for the songs. Worth mentioning is that you can perform these actions on multiple audio files at the same time. Squeed also packs a number of features designed to help you deal with certain repetitive tasks a lot faster. ![]() Batch rename, number, or tag tracks or import data from Discogs The best part is that you can readily copy all the metadata associated with a track and paste it to another via the contextual menu. Otherwise, the modifications will be lost. If you make any changes in the metadata fields, be sure to press the Save button. In addition, Squeed also offers you the possibility to preview the album cover or to listen to the track. ![]() Squeed provides support for working with the following parameters: title, artist, album, year, track number, comment, genre, album artist, composer, or publisher. You can see the complete list of songs in the Squeed main window.Įach time you select a particular track, on the left side of the Squeed main window you get to see the currently associated metadata information. Right off the bat, you must direct Squeed to the directory that includes the music collection you want to process: the utility automatically imports the audio files that come in a compatible format. Metadata editor that can scan folders for supported audio files The utility helps you tag and rename the tracks, can import metadata information from the Discogs online database, and automatically removes unused fields. Squeed is a metadata editing tool that is able to work with MP3, FLAC, AIFF, and M4A audio files.
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