Post-DAE: Anatomically Plausible Segmentation via Post-Processing With Denoising Autoencoders

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Multimodal dialogue segmentation with gesture post-processing

We investigate an automatic dialogue segmentation method using both verbal and non-verbal modalities. Dialogue contents are used for the initial segmentation of dialogue; then, gesture occurrences are used to remove the incorrect segment boundaries. A unique characteristic of our method is to use verbal and non-verbal information separately. We use a three-party dialogue that is rich in gesture...

متن کامل

Image Segmentation using Improved Imperialist Competitive Algorithm and a Simple Post-processing

Image segmentation is a fundamental step in many of image processing applications. In most cases the image’s pixels are clustered only based on the pixels’ intensity or color information and neither spatial nor neighborhood information of pixels is used in the clustering process. Considering the importance of including spatial information of pixels which improves the quality of image segmentati...

متن کامل

Acquisition Segmentation Feature Extraction Classification Post Processing Pre - Processing

Arabic script is the third most widely used writing system after Latin and Chinese, but research in Arabic Optical Character Recognition (OCR) is still nascent in comparison to Latin script. Arabic script is inherently cursive in nature, therefore techniques developed for other scripts are generally inappropriate for Arabic. In this paper we present recent progress in the field of Handwritten A...

متن کامل

Multimodal Stacked Denoising Autoencoders

We propose a Multimodal Stacked Denoising Autoencoder for learning a joint model of data that consists of multiple modalities. The model is used to extract a joint representation that fuses modalities together. We have found that this representation is useful for classification tasks. Our model is made up of layers of denoising autoencoders which are trained locally to denoise corrupted version...

متن کامل

Denoising Adversarial Autoencoders

Unsupervised learning is of growing interest because it unlocks the potential held in vast amounts of unlabelled data to learn useful representations for inference. Autoencoders, a form of generative model, may be trained by learning to reconstruct unlabelled input data from a latent representation space. More robust representations may be produced by an autoencoder if it learns to recover clea...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IEEE Transactions on Medical Imaging

سال: 2020

ISSN: 0278-0062,1558-254X

DOI: 10.1109/tmi.2020.3005297