Results 1 to 10 of about 95,087 (157)

HiMamba-Net: a Hilbert-serialized Mamba network for 3D point cloud instance segmentation [PDF]

Scientific Reports
Instance-level segmentation of large-scale 3D point clouds is a fundamental yet challenging task due to complex spatial structures, severe occlusions, and long-range dependencies.
Kai Zhao, Dai Shi, Yi Guo, Suzy Rogiers, Oula Ghannoum   +4 more
doaj   +2 more sources

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, Shadi Albarqouni   +2 more
exaly   +3 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

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   +3 more sources

Multiresolution segmentation of natural images: from linear to nonlinear scale-space representations [PDF]

IEEE Transactions on Image Processing, 2004
In this paper, we introduce a framework that merges classical ideas borrowed from scale-space and multiresolution segmentation with nonlinear partial differential equations. A non-linear scale-space stack is constructed by means of an appropriate diffusion equation.
P Vandergheynst
exaly   +5 more sources

A similarity-aware network with contrastive optimization for biomedical image segmentation [PDF]

BMC Medical Imaging
Background Accurate biomedical image segmentation is crucial for clinical diagnosis. Convolutional neural networks and Transformer-based models have been widely used for biomedical image segmentation and have improved segmentation accuracy across ...
Rongjia Lin, Zhidong Yang, Ziheng Xu, Na Gao, Rui Yan, Xiuhui Shi, Senlin Lin, Bowen Huang   +7 more
doaj   +2 more sources

MambaMeshSeg-Net: A Large-Scale Urban Mesh Semantic Segmentation Method Using a State Space Model with a Hybrid Scanning Strategy

Remote Sensing
Semantic segmentation of urban meshes plays an increasingly crucial role in the analysis and understanding of 3D environments. Most existing large-scale urban mesh semantic segmentation methods focus on integrating multi-scale local features but struggle
Wenjie Zi, Hao Chen, Jun Li, Jiangjiang Wu   +3 more
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

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   +1 more source