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Adaptive prototype and consistency alignment for semi-supervised domain adaptation
Unsupervised Domain Adaptation (UDA) aims to transfer knowledge from a label-rich source domain to an unlabeled target domain whose data...
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QuanCro: a novel framework for quantification of corn crops’ consistency under natural field conditions
Crop population and inter-plant spacing in corn farms can provide useful insight into plant phenotypic analysis and informed establishment decisions,...
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A contrastive autoencoder with multi-resolution segment-consistency discrimination for multivariate time series anomaly detection
Most reconstruction-based multivariate time series (MTS) anomaly detection methods tend to learn point-wise information, failing to extract a robust...
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Unsupervised Domain Adaptation Depth Estimation Based on Self-attention Mechanism and Edge Consistency Constraints
In the unsupervised domain adaptation (UDA) (Akada et al. Self-supervised learning of domain invariant features for depth estimation, in: 2022...
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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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Robust consistency learning for facial expression recognition under label noise
Label noise is inevitable in facial expression recognition (FER) datasets, especially for datasets that collected by web crawling, crowd sourcing in...
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Transactional-Turn Causal Consistency
Function-as-a-Service (FaaS, serverless) computing systems use an actor-like model that executes a function asynchronously, atomically and in an...
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Consistency Regularization for Domain Adaptation
Collection of real world annotations for training semantic segmentation models is an expensive process. Unsupervised domain adaptation (UDA) tries to...
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FedSEMA: similarity-aware for representation consistency in federated contrastive learning
Contrastive learning has emerged as a promising method for addressing the non-independent and identically distributed (non-IID) problem in federated...
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Single-Video Temporal Consistency Enhancement with Rolling Guidance
Image/video synthesis has been extensively studied in academics, and computer-generated videos are becoming increasingly popular among the general...
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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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Consistency Guided Multiview Hypergraph Embedding Learning with Multiatlas-Based Functional Connectivity Networks Using Resting-State fMRI
Recently, resting-state functional connectivity network (FCN) analysis via graph convolutional networks (GCNs) has greatly boosted diagnostic...
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Generalized Category Discovery with Clustering Assignment Consistency
Generalized category discovery (GCD) is an important open-world task to automatically cluster the unlabeled samples using information transferred...
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Multi-view subspace clustering with inter-cluster consistency and intra-cluster diversity among views
Multi-view subspace clustering aims to classify a collection of multi-view data drawn from a union of subspaces into their corresponding subspaces....
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NoSQL-based storage systems: influence of consistency on performance, availability and energy consumption
Big data applications have motivated the adoption of NoSQL database management systems (DBMS), which usually provide better performance and...
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Fairness and Liveness Under Weak Consistency
We consider the verification of concurrent programs running on weakly consistent platforms, i.e., weaker semantics than the classical Sequential...
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Relation-consistency graph convolutional network for image super-resolution
Convolutional neural networks (CNNs) have been widely exploited in single image super-resolution (SISR) due to their powerful feature representation...
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Image classification with consistency-regularized bad semi-supervised generative adversarial networks: a visual data analysis and synthesis
Semi-supervised learning, which entails training a model with manually labeled images and pseudo-labels for unlabeled images, has garnered...
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Multi-level consistency regularization for domain adaptive object detection
To improve the adaptability of detectors, most existing domain adaptation algorithms adopt adversarial learning to align feature distributions...
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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...
