Hongliang Li mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Image segmentation. In his study, Generalization is inextricably linked to Machine learning, which falls within the broad field of Artificial intelligence. His Pattern recognition research is multidisciplinary, relying on both Edge detection and Discrete cosine transform.
His study looks at the relationship between Computer vision and topics such as Robustness, which overlap with Automatic summarization, Semantic analysis, Face detection and Cut. His Feature extraction study which covers Image texture that intersects with Histogram and Scale space. As a part of the same scientific family, Hongliang Li mostly works in the field of Image segmentation, focusing on Similarity and, on occasion, Word error rate and SimRank.
Hongliang Li focuses on Artificial intelligence, Pattern recognition, Computer vision, Segmentation and Image segmentation. Feature extraction, Object detection, Image, Feature and Pascal are among the areas of Artificial intelligence where the researcher is concentrating his efforts. Hongliang Li works mostly in the field of Feature, limiting it down to topics relating to Image quality and, in certain cases, Distortion, Machine learning and Metric, as a part of the same area of interest.
His studies in Pattern recognition integrate themes in fields like Contextual image classification, Pixel, Histogram and Cluster analysis. Computer vision is frequently linked to Visualization in his study. His Segmentation research integrates issues from Object, Minimum bounding box, Embedding and Saliency map.
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Segmentation, Pascal and Computer vision. His study in Artificial intelligence focuses on Feature extraction, Feature, Image, Image segmentation and Object detection. His research investigates the connection between Pattern recognition and topics such as Object that intersect with problems in Sentence.
His study in Segmentation is interdisciplinary in nature, drawing from both Parsing, Classifier, Pixel, Embedding and Minimum bounding box. His work in Pascal tackles topics such as Convolutional neural network which are related to areas like Data mining and Disjoint sets. His study on Single image is often connected to Haze as part of broader study in Computer vision.
His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Pascal, Segmentation and Object detection. His Artificial intelligence study incorporates themes from Algorithm and Computer vision. He works in the field of Pattern recognition, namely Discriminative model.
The concepts of his Pascal study are interwoven with issues in Feature fusion, Image segmentation, Embedding, Cluster analysis and Binary classification. His biological study spans a wide range of topics, including Minimum bounding box and Convolutional neural network. The various areas that he examines in his Object detection study include Remote sensing and Detector.
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A Co-Saliency Model of Image Pairs
Hongliang Li;King Ngi Ngan.
IEEE Transactions on Image Processing (2011)
Waterloo Exploration Database: New Challenges for Image Quality Assessment Models
Kede Ma;Zhengfang Duanmu;Qingbo Wu;Zhou Wang.
IEEE Transactions on Image Processing (2017)
A Fast HEVC Inter CU Selection Method Based on Pyramid Motion Divergence
Jian Xiong;Hongliang Li;Qingbo Wu;Fanman Meng.
IEEE Transactions on Multimedia (2014)
Multimodal medical image fusion based on IHS and PCA
Changtao He;Quanxi Liu;Hongliang Li;Haixu Wang.
Procedia Engineering (2010)
Object Co-Segmentation Based on Shortest Path Algorithm and Saliency Model
Fanman Meng;Hongliang Li;Guanghui Liu;King Ngi Ngan.
IEEE Transactions on Multimedia (2012)
Blind Image Quality Assessment Based on Multichannel Feature Fusion and Label Transfer
Qingbo Wu;Hongliang Li;Fanman Meng;King N. Ngan.
IEEE Transactions on Circuits and Systems for Video Technology (2016)
Co-Salient Object Detection From Multiple Images
Hongliang Li;Fanman Meng;King Ngi Ngan.
IEEE Transactions on Multimedia (2013)
A Multiple Visual Models Based Perceptive Analysis Framework for Multilevel Video Summarization
Junyong You;Guizhong Liu;Li Sun;Hongliang Li.
IEEE Transactions on Circuits and Systems for Video Technology (2007)
Saliency model-based face segmentation and tracking in head-and-shoulder video sequences
Hongliang Li;King N. Ngan.
Journal of Visual Communication and Image Representation (2008)
LETRIST: Locally Encoded Transform Feature Histogram for Rotation-Invariant Texture Classification
Tiecheng Song;Hongliang Li;Fanman Meng;Qingbo Wu.
IEEE Transactions on Circuits and Systems for Video Technology (2018)
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