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Found 5 papers, 3 papers with code
From Pixels to Titles: Video Game Identification by Screenshots using Convolutional Neural Networks
This paper investigates video game identification through single screenshots, utilizing five convolutional neural network (CNN) architectures (MobileNet, DenseNet, EfficientNetB0, EfficientNetB2, and EfficientNetB3) across 22 home console systems, spanning from Atari 2600 to PlayStation 5.
On tuning a mean-field model for semi-supervised classification
Semi-supervised learning (SSL) has become an interesting research area due to its capacity for learning in scenarios where both labeled and unlabeled data are available.
COVID-19 Detection on Chest X-Ray Images: A comparison of CNN architectures and ensembles
These were further increased to 99. 25% and 99. 24%, respectively, through an ensemble with five instances of DenseNet169.
Visually Impaired Aid using Convolutional Neural Networks, Transfer Learning, and Particle Competition and Cooperation
We also propose a dataset to train the classifiers, including indoor and outdoor situations with different types of light, floor, and obstacles.
Building Networks for Image Segmentation using Particle Competition and Cooperation
Computer simulations are performed on some real-world images from the Microsoft GrabCut database, and the segmentation results related in this paper show the effectiveness of the proposed method.
