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Claim this profileWorks160 from public data
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- Unbiased Mean Teacher for Cross-domain Object Detection423
A new Unbiased Mean Teacher (UMT) model for cross-domain object detection is proposed, revealing that there often exists a considerable model bias for the simple mean teacher (MT) model in cross- domain scenarios, and eliminating the model bias with several simple yet highly effective strategies.
- Domain adaptation from multiple sources via auxiliary classifiers339
A new data-dependent regularizer based on smoothness assumption into Least-Squares SVM (LS-SVM), which enforces that the target classifier shares similar decision values with the auxiliary classifiers from relevant source domains on the unlabeled patterns of the target domain.
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- Constructing Self-Motivated Pyramid Curriculums for Cross-Domain Semantic Segmentation: A Non-Adversarial Approach239
This work proposes a new approach, called self-motivated pyramid curriculum domain adaptation (PyCDA), to facilitate the adaptation of semantic segmentation neural networks from synthetic source domains to real target domains and reports state-of-the-art results for the adaptation from both GTAV and SYNTHIA to Cityscapes.
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- An experimental study on breast lesion detection and classification from ultrasound images using deep learning architectures179
Evaluating several existing state-of-the-art object detection and classification methods for breast lesions CAD reveals that better and more efficient detection and convolutional neural network (CNN) frameworks is one important factor for better performance of detecting and classification task of the breast lesion.
- STST: Spatial-Temporal Specialized Transformer for Skeleton-based Action Recognition147
A multi-task self-supervised learning method is proposed by providing confusing samples in different situations to improve the robustness of the model and demonstrate the improved performances and analysis of the proposed method.
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- Webly-Supervised Video Recognition by Mutually Voting for Relevant Web Images and Web Video Frames104
A novel approach to mutually voting for relevant Web images and video frames, where two forces are balanced, i.e. aggressive matching and passive video frame selection is proposed and validated on three large-scale video recognition datasets.
- A survey on computer aided diagnosis for ocular diseases96
While CAD for ocular diseases has shown considerable progress over the past years, the clinical importance of fully automatic CAD systems which are able to embed clinical knowledge and integrate heterogeneous data sources still show great potential for future breakthrough.
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- Detecting retinal microaneurysms and hemorrhages with robustness to the presence of blood vessels81
Improved lesion detection using the proposed approach can help in automatic detection of Diabetic Retinopathy by applying the proposed filters on patches of different sizes instead of filtering the full image.
- Optic Cup Segmentation for Glaucoma Detection Using Low-Rank Superpixel Representation73
This work presents an unsupervised approach to segment optic cups in fundus images for glaucoma detection without using any additional training images and develops an adaptive strategy for automatically choosing the only parameter in LRR and obtaining the final result for each image.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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