IEEE

Optimized KiU-Net: A Convolutional Autoencoder for Retinal Vessel Segmentation in Medical Images

Abstract: Medical image segmentation plays a central role in enhancing diagnosis, surgical planning, and treatment strategies, and in this work, the focus is on segmenting retinal vessels from color ...
Scientific Research Publishing

Xu, J., Xiang, L., Liu, Q., Gilmore, H., Wu, J., Tang, J., et al. (2016) Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images. IEEE ...

ABSTRACT: Liver cancer is one of the most prevalent and lethal forms of cancer, making early detection crucial for effective treatment. This paper introduces a novel approach for automated liver tumor ...
IEEE

MAFS: Masked Autoencoder for Infrared-Visible Image Fusion and Semantic Segmentation

Abstract: Infrared-visible image fusion methods aim at generating fused images with good visual quality and also facilitate the performance of high-level tasks. Indeed, existing semantic-driven ...
GitHub

Random Segmentation fault in test_masked_autoencoder_vit

[2025-06-17T20:37:02.135Z] Starting test: test_access_attn_matrix (tests.test_masked_autoencoder_vit.TestMaskedAutoencoderViT)... [2025-06-17T20:37:02.135Z] 2025-06 ...
Scientific Research Publishing

Sun, Y., Xue, B., Zhang, M. and Yen, G.G. (2019) A Particle Swarm Optimization-Based Flexible Convolutional Autoencoder for Image Classification. IEEE Transactions on Neural ...

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...