This paper discusses the task of enhancing malaria detection in thick blood smear images by proposing a UNet-based denoising algorithm. Noise and artifacts in these images can compromise the accuracy ...
The developed model modified Schrödinger bridge-type diffusion models to add noise to real data through the encoder and reconstructed samples through the decoder. It uses two objective functions, the ...
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Image Denoising with Autoencoders in R (University Project) Built a convolutional autoencoder in R using Keras/TensorFlow to perform image denoising on MNIST and CIFAR-10 datasets with varying levels ...
Abstract: Deep learning models have achieved groundbreaking results in computer vision; however, their vulnerability to adversarial examples persists. Adversarial examples, generated by adding minute ...
ABSTRACT: The rapid growth of unlabeled time-series data in domains such as wireless communications, radar, biomedical engineering, and the Internet of Things (IoT) has driven advancements in ...
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