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Found 6 papers, 2 papers with code
Disentangling Hippocampal Shape Variations: A Study of Neurological Disorders Using Graph Variational Autoencoder with Contrastive Learning
This research provides valuable insights into the relationship between neurological disorder and hippocampal shape changes in different age groups of MS populations using a Graph VAE with Supervised Contrastive loss.
Forecasting Pressure Of Ventilator Using A Hybrid Deep Learning Model Built With Bi-LSTM and Bi-GRU To Simulate Ventilation
As a result, predicting a patient's ventilator pressure is essential when designing a simulation ventilator.
Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods
However, English is the predominant language for online resources and technical knowledge, journals, and documentation.
Human Activity Analysis and Recognition from Smartphones using Machine Learning Techniques
Different types of machine learning models are used for this purpose, and this is a part of analyzing human behavior through machines.
Recent Advances in Deep Learning Techniques for Face Recognition
We discuss the papers related to different algorithms, architectures, loss functions, activation functions, datasets, challenges, improvement ideas, current and future trends of DL-based FR systems.
Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network
Inspired by the success of edge enhanced GAN (EEGAN) and ESRGAN, we apply a new edge-enhanced super-resolution GAN (EESRGAN) to improve the image quality of remote sensing images and use different detector networks in an end-to-end manner where detector loss is backpropagated into the EESRGAN to improve the detection performance.
