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Works16 from public data
- Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition932
A novel Region Attention Network (RAN), to adaptively capture the importance of facial regions for occlusion and pose variant FER, and a region biased loss to encourage high attention weights for the most important regions.
- Region Generation and Assessment Network for Occluded Person Re-Identification88
A Region Generation and Assessment Network (RGANet) to effectively and efficiently detect the human body regions and highlight the important regions is proposed and extensive experimental results demonstrate the superiority of RGANet against state-of-the-art methods.
- Development of a virtual reality platform for effective communication of structural data in drug discovery69
By reducing the barriers to viewing and interacting with structural data, structural analysis can be democratized to a general scientist, which in turn fosters novel collaboration, ideas, and findings in structural biology and structure-based drug discovery.
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- Summarizing Stream Data for Memory-Constrained Online Continual Learning35
This work proposes to Summarize the knowledge from the Stream Data (SSD) into more informative samples by distilling the training characteristics of real images through maintaining the consistency of training gradients and relationship to the past tasks.
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- The Snowflake Hypothesis: Training and Powering GNN with One Node One Receptive Field8
The Snowflake Hypothesis -- a novel paradigm underpinning the concept of "one node, one receptive field'' is introduced, proposing a corresponding uniqueness in the receptive fields of nodes in the GNNs.
- Analysis of Heart-Sound Characteristics during Motion Based on a Graphic Representation5
This paper provides several characteristic parameters that are both sensitive and insensitive (such as sound-direction vector, state-change-trend diagram, and difference value) to motion, thus providing a new technique for the diverse analysis of heart sounds in motion.
- A 3D ear recognition method based on auricle structural feature3
Experimental results conducted on University of Notre Dame biometric datasets collection F and collection G outperform the state-of-the-art 3D ear recognitions based on ICP and demonstrate that the proposed method is more robust to pose variation than the state of theart.
- 3D Pure Ear Extraction and Recognition2
A new edge-based approach is proposed to extract the pure ear automatically, using both the edge information form the intensity images and depth images, and the well-known ICP algorithm is applied for recognition.
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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 2026-10-11. 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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