Results 1 to 10 of about 572,703 (195)

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 ...
Benedikt Wiestler, Christoph Baur, Nassir Navab   +2 more
exaly   +5 more sources

Object-Based Change Detection in Urban Areas: The Effects of Segmentation Strategy, Scale, and Feature Space on Unsupervised Methods

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, Xiaoxue Ma, Dirk Tiede, Liang Cheng, Zhenjie Chen, Dong Chen   +7 more
doaj   +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, Ming Zhu, Jing Wang, Xiangji Guo, Yifan Yang, Jiarong Wang   +5 more
doaj   +2 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, Cousty, Jean, Vaillant, Régis, Najman, Laurent   +3 more
openaire   +4 more sources

Remote Sensing Image Segmentation Using Vision Mamba and Multi-Scale Multi-Frequency Feature Fusion

Remote Sensing
Rapid 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, Chenchen Liu, Zhenhua Wu, Lei Zhang, Lixia Yang   +4 more
doaj   +3 more sources

Double-Branch Multi-Scale Contextual Network: A Model for Multi-Scale Street Tree Segmentation in High-Resolution Remote Sensing Images

Sensors
Street 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
doaj   +2 more sources

LTM-UNet: Linear Transformer–Mamba with Attention-Based U-Net for Context-Aware Breast Ultrasound Image Segmentation [PDF]

Diagnostics
Background/Objectives: Accurate breast lesion segmentation using deep learning models requires precise understanding of both global contextual relevance and finer lesion structure details, which remains a challenge for existing convolutional and ...
Shivpratap Singh Kushwah, Santosh Prakash Chouhan, Narinder Singh Punn, Mahua Bhattacharya   +3 more
doaj   +2 more sources

SADNet: Space-aware DeepLab network for Urban-Scale point clouds semantic segmentation

International Journal of Applied Earth Observations and Geoinformation
Semantic segmentation of urban-scale point clouds can effectively assist people in understanding and perceiving 3D urban scenes. Although a considerable number of deep learning models for the semantic segmentation of point clouds have been proposed, some
Wenxiao Zhan, Jing Chen
doaj   +3 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, Jim Tørresen, Jim Tørresen, Ulysse Côté-Allard, Ulysse Côté-Allard   +4 more
doaj   +1 more source