all AI news
Robust image segmentation model based on binary level set
March 21, 2024, 4:45 a.m. | Wenqi Zhao
cs.CV updates on arXiv.org arxiv.org
Abstract: In order to improve the robustness of traditional image segmentation models to noise, this paper models the illumination term in intensity inhomogeneity images. Additionally, to enhance the model's robustness to noisy images, we incorporate the binary level set model into the proposed model. Compared to the traditional level set, the binary level set eliminates the need for continuous reinitialization. Moreover, by introducing the variational operator GL, our model demonstrates better capability in segmenting noisy images. …
abstract arxiv binary cs.cv image images intensity noise paper robust robustness segmentation set type
More from arxiv.org / cs.CV updates on arXiv.org
Multi-View Spectrogram Transformer for Respiratory Sound Classification
2 days, 19 hours ago |
arxiv.org
GaussianHead: High-fidelity Head Avatars with Learnable Gaussian Derivation
2 days, 19 hours ago |
arxiv.org
OTMatch: Improving Semi-Supervised Learning with Optimal Transport
2 days, 19 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Senior Machine Learning Engineer
@ GPTZero | Toronto, Canada
ML/AI Engineer / NLP Expert - Custom LLM Development (x/f/m)
@ HelloBetter | Remote
Doctoral Researcher (m/f/div) in Automated Processing of Bioimages
@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena
Seeking Developers and Engineers for AI T-Shirt Generator Project
@ Chevon Hicks | Remote
Principal Data Architect - Azure & Big Data
@ MGM Resorts International | Home Office - US, NV
GN SONG MT Market Research Data Analyst 11
@ Accenture | Bengaluru, BDC7A