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
doaj +1 more source
Research of segmentation method on color image of Lingwu long jujubes based on the maximum entropy
EURASIP Journal on Image and Video Processing, 2017 This paper researches on methods of the color image segmentation method of Lingwu long jujubes based on the maximum entropy to achieve the accuracy of image segmentation and improve accuracy of machine recognition.
Yutan Wang +5 more
doaj +1 more source
Hierarchical image simplification and segmentation based on Mumford-Shah-salient level line selection [PDF]
, 2016 Hierarchies, such as the tree of shapes, are popular representations for image simplification and segmentation thanks to their multiscale structures. Selecting meaningful level lines (boundaries of shapes) yields to simplify image while preserving intact
Géraud, Thierry +2 more
core +2 more sources
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
doaj +1 more source
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
doaj +1 more source
Medical Image Segmentation Based on Transformer and HarDNet Structures
IEEE Access, 2023 Medical image segmentation is a crucial way to assist doctors in the accurate diagnosis of diseases. However, the accuracy of medical image segmentation needs further improvement due to the problems of many noisy medical images and the high similarity ...
Tongping Shen, Huanqing Xu
doaj +1 more source
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
core +1 more source
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
core +3 more sources
WAILS: Watershed Algorithm With Image-Level Supervision for Weakly Supervised Semantic Segmentation
IEEE Access, 2019 Image semantic segmentation has great development in many fields, and the lack of fully supervised segmentation labels has always been a major problem in the development of image semantic segmentation.
Hongming Zhou +4 more
doaj +1 more source
DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation [PDF]
2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS), 2020 Semantic image segmentation is the process of labeling each pixel of an image with its corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a popular strategy for solving medical image segmentation tasks. To improve the
Debesh Jha +4 more
semanticscholar +1 more source