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Found 6 papers, 1 papers with code
Multimodal SuperCon: Classifier for Drivers of Deforestation in Indonesia
In this work, we propose a contrastive learning architecture, called Multimodal SuperCon, for classifying drivers of deforestation in Indonesia using satellite images obtained from Landsat 8.
Optimization of Convolutional Neural Network using Microcanonical Annealing Algorithm
The performance of the proposed method is tested using the MNIST and CIFAR-10 datasets.
Ischemic Stroke Identification Based on EEG and EOG using 1D Convolutional Neural Network and Batch Normalization
Because of the availability, another device that potential to diagnose stroke in Indonesia is EEG.
Metaheuristic Algorithms for Convolution Neural Network
Furthermore, the proposed methods are also compared with the original CNN.
Sequence-based Sleep Stage Classification using Conditional Neural Fields
Treating the sleep signals as sequences, this paper compared two powerful unsupervised feature extractors and three sequence-based classifiers regarding accuracy and computational (training and testing) time after 10-folds cross-validation.
Combining Generative and Discriminative Neural Networks for Sleep Stages Classification
In this study, we used two datasets: an open data set that is treated as a benchmark; the other dataset is our sleep stages dataset (available for download) to verify the results further.
