Image segmentation with a multilevel threshold using backtracking search optimization algorithm
Tikrit Journal of Pure Science, 2020 Image segmentation is an important process in image processing. Though, there are many applications are affected by the segmentation methods and algorithms, unfortunately, not one technique, but the threshold is the popular one.
Hather Ibraheem Abed
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Multilevel thresholding image segmentation algorithm based on Mumford–Shah model
Journal of Intelligent Systems, 2023 Image segmentation is one of the important tasks of computer vision and computer image processing, and the purpose of image segmentation is to achieve the extraction and recognition of the target image region.
Kang Xiancai, Hua Chuangli
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Brain tumor segmentation based on a hybrid clustering technique
Egyptian Informatics Journal, 2015 Image segmentation refers to the process of partitioning an image into mutually exclusive regions. It can be considered as the most essential and crucial process for facilitating the delineation, characterization, and visualization of regions of interest
Eman Abdel-Maksoud +2 more
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An Image Segmentation Method for Global Vision Robot Fish Competition
MATEC Web of Conferences, 2018 Image segmentation is a key link of vision system of the global vision bionic robot fish, and a precondition of target localization and tracking. In this paper, we propose a visual threshold method for color image segmentation.
Jia Yifan, Li Juanjuan, Hu Liang
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Review of Deep Learning Applications in Spinal Image Segmentation [PDF]
Jisuanji gongchengDeep learning algorithms have the advantages of strong learning, strong adaptive, and unique nonlinear mapping abilities in spinal image segmentation.
Baihao JIANG, Jing LIU, Dawei QIU, Liang JIANG
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Survey of Image Semantic Segmentation Methods Based on Deep Neural Network
Jisuanji kexue yu tansuo, 2021 Image semantic segmentation is a hot research topic in the field of computer vision in recent years. With the rise of deep learning technology, image semantic segmentation and deep learning technology are integrated and developed, which has made ...
XU Hui, ZHU Yuhua, ZHEN Tong, LI Zhihui
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Segmentation of multi-temporal polarimetric SAR data based on mean-shift and spectral graph partitioning [PDF]
PeerJ, 2022 Polarimetric SAR (PolSAR) image segmentation is a key step in its interpretation. For the targets with time series changes, the single-temporal PolSAR image segmentation algorithm is difficult to provide correct segmentation results for its target ...
Caiqiong Wang +4 more
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Statistical Region Based Segmentation of Ultrasound Images [PDF]
, 2008 Segmentation of ultrasound images is a challenging problem due to speckle, which corrupts the image and can result in weak or missing image boundaries, poor signal to noise ratio, and diminished contrast resolution.
Ayed +30 more
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DCSLK: Combined large kernel shared convolutional model with dynamic channel Sampling
NeuroImageThis study centers around the competition between Convolutional Neural Networks (CNNs) with large convolutional kernels and Vision Transformers in the domain of computer vision, delving deeply into the issues pertaining to parameters and computational ...
Zongren Li +3 more
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A Latent Source Model for Patch-Based Image Segmentation
, 2015 Despite the popularity and empirical success of patch-based nearest-neighbor and weighted majority voting approaches to medical image segmentation, there has been no theoretical development on when, why, and how well these nonparametric methods work.
Chen, George +2 more
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