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A novel transformer-based few-shot learning method for intelligent fault diagnosis with noisy labels under varying working conditions
Recent years have witnessed the success of Few-shot Learning (FSL) methods in
equipment reliability enhancement and fault diagnosis, by virtue of learning from limited data …
equipment reliability enhancement and fault diagnosis, by virtue of learning from limited data …
A semantic perception and CNN-transformer hybrid network for occluded person re-identification
The objective of the occluded person re-identification (ReID) task is to capture the same
person from different camera angles when the pedestrian's body is partially occluded. In this …
person from different camera angles when the pedestrian's body is partially occluded. In this …
Dual clustering co-teaching with consistent sample mining for unsupervised person re-identification
In unsupervised person Re-ID, peer-teaching strategy leveraging two networks to facilitate
training has been proven to be an effective method to deal with the pseudo label noise …
training has been proven to be an effective method to deal with the pseudo label noise …
Superpixel-wise contrast exploration for salient object detection
Y Qiu, J Mei, J Xu - Knowledge-Based Systems, 2024 - Elsevier
Salient object detection (SOD) methods typically consider SOD as a pixel-wise binary
classification problem and utilize the binary cross-entropy (BCE) loss for optimization …
classification problem and utilize the binary cross-entropy (BCE) loss for optimization …
Source-free style-diversity adversarial domain adaptation with privacy-preservation for person re-identification
Unsupervised domain adaptation (UDA) techniques for person re-identification (ReID) have
been extensively studied to facilitate the transfer of knowledge from labeled source domains …
been extensively studied to facilitate the transfer of knowledge from labeled source domains …
[HTML][HTML] Human-in-the-loop cross-domain person re-identification
Person re-identification is a challenging cross-camera matching problem, which is inherently
subject to domain shift. To mitigate it, many solutions have been proposed so far, based on …
subject to domain shift. To mitigate it, many solutions have been proposed so far, based on …
Hierarchical camera-aware contrast extension for unsupervised person re-identification
Unsupervised person re-identification (Re-ID) targets to learn discriminative representations
without annotations. Recently, clustering-based methods have shown promising …
without annotations. Recently, clustering-based methods have shown promising …
Knowledge Consistency Distillation for Weakly Supervised One Step Person Search
Weakly supervised person search targets to detect and identify a person with only bounding
box annotations. Recent approaches have focused on learning person relations in a single …
box annotations. Recent approaches have focused on learning person relations in a single …
Reliable cross-camera learning in random camera person re-identification
Most existing person re-identification (Re-ID) methods rely on high-cost manual annotations.
To overcome the applicable issue, we focus on a novel semi-supervised Re-ID without cross …
To overcome the applicable issue, we focus on a novel semi-supervised Re-ID without cross …
Deep Mutual Distillation for Unsupervised Domain Adaptation Person Re-identification
Unsupervised domain adaptation person re-identification (UDA person re-ID) aims at
transferring the knowledge on the source domain with expensive manual annotation to the …
transferring the knowledge on the source domain with expensive manual annotation to the …