Results 101 to 110 of about 12,457,928 (304)
3D medical volume segmentation using hybrid multiresolution statistical approaches [PDF]
, 2010 This article is available through the Brunel Open Access Publishing Fund. Copyright © 2010 S AlZu’bi and A Amira.3D volume segmentation is the process of partitioning voxels into 3D regions (subvolumes) that represent meaningful physical entities which ...
Alzubi, S +3 more
core +1 more source
Explainable multi-module semantic guided attention based network for medical image segmentation
, 2022 Automated segmentation of medical images is crucial for disease diagnosis and treatment planning. Medical image segmentation has been improved based on the convolutional neural networks (CNNs) models. Unfortunately, they are still limited by scenarios in
Karri, Meghana +2 more
core +1 more source
Advanced Science, EarlyView.A flexible pressure sensor with triple‐gradient design of conductivity, modulus, and dimension in binary micro‐dome pixels is proposed. Based on precisely‐designed CNT/PDMS matrix, the device exhibits a linear sensitivity of 974.1 kPa−1 across range up to 1.8 MPa (R2 > 0.99), offering an effective strategy for potential applications in healthcare ...
Yifan Liu +9 more
wiley +1 more source
Side information-driven image coding for hybrid machine–human vision
EURASIP Journal on Image and Video ProcessingWith the development of machine learning, advanced photography and image transmission systems, images are being processed more and more by machines, so image coding for machines (ICM) came into being.
Zhongpeng Zhang +2 more
doaj +1 more source
Advanced Science, EarlyView.Technical limitations often let dominant signals overshadow rare cell types and fine‐grained heterogeneity in spatial transcriptomics. SemanticST, a graph neural network using multi‐semantic graph fusion and a novel min‐cut loss, recovers these subtle patterns.
Roxana Zahedi +7 more
wiley +1 more source
Semantic and Structural Image Segmentation for Prosthetic Vision
Jornada de Jóvenes Investigadores del I3A, 2019 We present a new approach to build a schematic representation of indoor environments for phosphene images. The proposed method combines a variety of convolutional neural networks for extracting and conveying relevant information about the scene such as structural informative edges of the environment and silhouettes of segmented objects.
Melani Sanchez-Garcia +2 more
openaire +7 more sources
Multi-scale Gaussian representation and outline-learning based cell image segmentation [PDF]
, 2013 BACKGROUND: High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies.
Rämö, P. +17 more
core +1 more source
Learning Work Function via Implicit Reasoning on Electrostatic Potential Landscapes
Advanced Science, EarlyView.StructPot‐CLR establishes a cross‐modal contrastive learning framework that aligns the crystal structures of 2D materials with plane‐averaged electrostatic potential landscapes for physically informed work‐function prediction. The model achieves an MAE of 0.265 eV and an R2 of 0.902 on the held‐out test set while accurately preserving key morphological
Haoyu Wan, Yue Wu, Tianhao Su, Deng Pan
wiley +1 more source
A multilevel segmentation method of asymmetric semantics based on deep learning
IET Cyber-Physical SystemsAn asymmetric semantic multi‐level segmentation method based on depth learning is proposed in order to improve the precision and effect of semantic segmentation.
Angxin Liu, Yongbiao Yang
doaj +1 more source
Semi-MedSeq: Semi-supervised Semantic Segmentation for Medical Image Sequences
, 2023 Semi-MedSeq: Semi-supervised Semantic Segmentation for Medical Image ...
Q Li (6964538) +7 more
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