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Multi-scale constraints and perturbation consistency for semi-supervised sonar image segmentation
Emerging semi-supervised learning methods have enabled great progress in segmentation tasks. However, popular semi-supervised segmentation models use...
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Perturbation consistency and mutual information regularization for semi-supervised semantic segmentation
Recent semi-supervised learning has attracted much attention by leveraging the hidden structures learned from unlabeled data to reduce the number of...
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Spatiotemporal Perturbation Based Dynamic Consistency for Semi-supervised Temporal Action Detection
Temporal action detection usually relies on huge tagging costs to achieve significant performance. Semi-supervised learning, where only a small...
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Semi-supervised Retinal Vessel Segmentation Through Point Consistency
Retinal vessels usually serve as biomarkers for early diagnosis and treatment of ophthalmic and systemic diseases. However, collecting and labeling...
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Analytical solution for ginzburg–landau equation in discrete solitons laser arrays lattices via non-perturbation methods
The Ginzburg–Landau equation (GLE) plays an important role in discrete solitons laser array lattices. In this manuscript, the analytical solution for...
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On Robust Cross-view Consistency in Self-supervised Monocular Depth Estimation
Remarkable progress has been made in self-supervised monocular depth estimation (SS-MDE) by exploring cross-view consistency, e.g., photometric...
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Reliability-Adaptive Consistency Regularization for Weakly-Supervised Point Cloud Segmentation
Weakly-supervised point cloud segmentation with extremely limited labels is highly desirable to alleviate the expensive costs of collecting densely...
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Neuron-Level Inverse Perturbation Against Adversarial Attacks
Although deep learning models have achieved unprecedented success, their vulnerabilities towards adversarial attacks have attracted increasing...
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Exploring Epipolar Consistency Conditions
Intravital X-ray microscopy (XRM) in preclinical mouse models is of vital importance for the identification of microscopic structural pathological...
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AP-GCL: Adversarial Perturbation on Graph Contrastive Learning
A serious ecological hazard of illegal transactions (money laundering, financial fraud, etc.) on the Bitcoin trading network. Anti-money laundering...
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Towards continuous consistency axiom
It is shown for the first time in this paper, that Kleinberg’s (
2002 ) (self-contradictory) axiomatic system for distance-based clustering fails (that...
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Style-Hallucinated Dual Consistency Learning: A Unified Framework for Visual Domain Generalization
Domain shift widely exists in the visual world, while modern deep neural networks commonly suffer from severe performance degradation under domain...
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Semi-supervised 3D shape segmentation with multilevel consistency and part substitution
The lack of fine-grained 3D shape segmentation data is the main obstacle to develo** learning-based 3D segmentation techniques. We propose an...
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Learning on heterogeneous graph neural networks with consistency-based augmentation
Heterogeneous Graph Neural Networks(HGNNs), as an effective tool for mining heterogeneous graphs, have achieved remarkable performance on series of...
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Contrastive Perturbation Network for Weakly Supervised Temporal Sentence Grounding
The purpose of temporal sentence grounding is to find the most relevant temporal period corresponding to the natural language query in an unmodified...
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Smoothness-based consistency learning for macaque pose estimation
Macaques are a rare substitute and play an important role in study of human psychology and spiritual science. Accurate estimation of macaque pose...
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Prototype Consistency Learning for Medical Image Segmentation by Cross Pseudo Supervision
Due to the acquisition of anatomical/pathological labels is expensive and time-consuming, semi-supervised semantic segmentation is commonly utilized...
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Decoupled Consistency for Semi-supervised Medical Image Segmentation
By fully utilizing unlabeled data, the semi-supervised learning (SSL) technique has recently produced promising results in the segmentation of...
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RPUC: Semi-supervised 3D Biomedical Image Segmentation Through Rectified Pyramid Unsupervised Consistency
Deep learning models have demonstrated remarkable performance in various biomedical image segmentation tasks. However, their reliance on a large...
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Towards sustainable adversarial training with successive perturbation generation
Adversarial training with online-generated adversarial examples has achieved promising performance in defending adversarial attacks and improving...