9 Result(s)
within
Computer Science
Artificial Intelligence
Pattern Recognition
Yanwei Pang
Chapter
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Chapter and Conference Paper
Neighborhood Preserving Projections (NPP): A Novel Linear Dimension Reduction Method
Dimension reduction is a crucial step for pattern recognition and information retrieval tasks to overcome the curse of dimensionality. In this paper a novel unsupervised linear dimension reduction method, Neighbo...
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Chapter and Conference Paper
Balance between Diversity and Relevance for Image Search Results
Image search reranking has received great attention since it overcomes the drawback of “only textual features utilization” in nowadays web-scale image search engines. Most of existing methods focus on relevanc...
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Chapter and Conference Paper
Weighted Deformable Part Model for Robust Human Detection
Due to human pose articulation, variation in human shapes and appearances, especially occlusion between human and objects, one challenging problem in human detection is detect partially or completely occluded ...
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Chapter and Conference Paper
Frequency Domain Directional Filtering Based Rain Streaks Removal from a Single Color Image
Bad weather conditions, such as rain or snow, degrade outdoor vision system performance. Rain removal from a single image has been investigated extensively. However, existing built rain streak models are great...
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Chapter and Conference Paper
Interactive Head 3D Reconstruction Based Combine of Key Points and Voxel
In the 3D reconstruction of the head, we can extract a large number of key points from the face, but not enough key points from the hair. The 3D reconstruction method based key points do well in the facial rec...
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Chapter and Conference Paper
ECG Waveform Extraction from Paper Records
Electrocardiogram (ECG) is one of the most practiced methods to detect any abnormalities in human heart function. ECG waveforms are usually recorded as paper form. However, ECG paper records are inconvenient f...
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Chapter and Conference Paper
ET-Net: A Generic Edge-aTtention Guidance Network for Medical Image Segmentation
Segmentation is a fundamental task in medical image analysis. However, most existing methods focus on primary region extraction and ignore edge information, which is useful for obtaining accurate segmentation....
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Chapter and Conference Paper
Count- and Similarity-Aware R-CNN for Pedestrian Detection
Recent pedestrian detection methods generally rely on additional supervision, such as visible bounding-box annotations, to handle heavy occlusions. We propose an approach that leverages pedestrian count and pr...
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Chapter and Conference Paper
Illumination-Guided Transformer-Based Network for Multispectral Pedestrian Detection
Multi-modal information (e.g., visible and thermal) can generate reliable and robust pedestrian detection results in various computer vision applications. Despite its broad applications, it remains a crucial p...
