Results 1 to 10 of about 844,937 (315)
Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI [PDF]
Lecture Notes in Computer Science, 2020 Brain pathologies can vary greatly in size and shape, ranging from few pixels (i.e. MS lesions) to large, space-occupying tumors. Recently proposed Autoencoder-based methods for unsupervised anomaly segmentation in brain MRI have shown promising performance, but face difficulties in modeling distributions with high fidelity, which is crucial for ...
Christoph Baur +2 more
exaly +4 more sources
Remote Sensing, 2016 Object-based change detection (OBCD) has recently been receiving increasing attention as a result of rapid improvements in the resolution of remote sensing data.
Lei Ma, Manchun Li, Thomas Blaschke
exaly +4 more sources
Scale-space for empty catheter segmentation in PCI fluoroscopic images [PDF]
International Journal of Computer Assisted Radiology and Surgery, 2017 In this article, we present a method for empty guiding catheter segmentation in fluoroscopic X-ray images. The guiding catheter, being a commonly visible landmark, its segmentation is an important and a difficult brick for Percutaneous Coronary Intervention (PCI) procedure modeling.In number of clinical situations, the catheter is empty and appears as ...
Bacchuwar, Ketan +3 more
openaire +4 more sources
Multi-Scale Deep Neural Network Based on Dilated Convolution for Spacecraft Image Segmentation
Sensors, 2022 In recent years, image segmentation techniques based on deep learning have achieved many applications in remote sensing, medical, and autonomous driving fields.
Yuan Liu +5 more
semanticscholar +3 more sources
Remote Sensing Image Segmentation Using Vision Mamba and Multi-Scale Multi-Frequency Feature Fusion
Remote SensingRapid advancements in remote sensing (RS) imaging technology have heightened the demand for the precise and efficient interpretation of large-scale, high-resolution RS images. Although segmentation algorithms based on convolutional neural networks (CNNs)
Yice Cao +4 more
semanticscholar +4 more sources
SensorsStreet trees are of great importance to urban green spaces. Quick and accurate segmentation of street trees from high-resolution remote sensing images is of great significance in urban green space management. However, traditional segmentation methods can
Hongyang Zhang, Shuo Liu
semanticscholar +3 more sources
Journal of Structural Biology, 2010 Cryo-electron microscopy produces 3D density maps of molecular machines, which consist of various molecular components such as proteins and RNA. Segmentation of individual components in such maps is a challenging task, and is mostly accomplished ...
Grigore D Pintilie +2 more
exaly +2 more sources
Image Semantic Segmentation Based on Multi-level Superposition and Attention Mechanism [PDF]
Jisuanji gongcheng, 2023 To address the common problems such as small-scale targets being easily lost and boundary segmentation being discontinuous owing to the complexity of target space, a semantic image segmentation model based on multi-level superposition and attention ...
Xiaodong SU, Shizhou LI, Jiayuan ZHAO, Hongyu LIANG, Yurong ZHANG, Hongyan XU
doaj +1 more source
Latent space unsupervised semantic segmentation
Frontiers in Physiology, 2023 The development of compact and energy-efficient wearable sensors has led to an increase in the availability of biosignals. To effectively and efficiently analyze continuously recorded and multidimensional time series at scale, the ability to perform ...
Knut J. Strommen +4 more
doaj +1 more source
Scale-Equivariant UNet for Histopathology Image Segmentation [PDF]
GEOmedia, 2023 Digital histopathology slides are scanned and viewed under different magnifications and stored as images at different resolutions. Convolutional Neural Networks (CNNs) trained on such images at a given scale fail to generalise to those at different ...
Yi-Lun Yang +2 more
semanticscholar +1 more source