Chih‐Cheng Hung

2.6k total citations
130 papers, 1.7k citations indexed

About

Chih‐Cheng Hung is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Chih‐Cheng Hung has authored 130 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Computer Vision and Pattern Recognition, 44 papers in Media Technology and 40 papers in Artificial Intelligence. Recurrent topics in Chih‐Cheng Hung's work include Remote-Sensing Image Classification (33 papers), Medical Image Segmentation Techniques (30 papers) and Image Retrieval and Classification Techniques (21 papers). Chih‐Cheng Hung is often cited by papers focused on Remote-Sensing Image Classification (33 papers), Medical Image Segmentation Techniques (30 papers) and Image Retrieval and Classification Techniques (21 papers). Chih‐Cheng Hung collaborates with scholars based in United States, China and Taiwan. Chih‐Cheng Hung's co-authors include Bor‐Chen Kuo, Enmin Song, Cheng‐Hsuan Li, Hsin-Hua Ho, J.S. Taur, Xiangyang Xu, Guangzhi Ma, Renchao Jin, Haichao Cao and Hong Liu and has published in prestigious journals such as Scientific Reports, The Journal of the Acoustical Society of America and IEEE Access.

In The Last Decade

Chih‐Cheng Hung

121 papers receiving 1.6k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Chih‐Cheng Hung 592 440 381 374 287 130 1.7k
Mohamad Mahmoud Al Rahhal 651 1.1× 442 1.0× 157 0.4× 487 1.3× 118 0.4× 44 1.9k
Albert C. S. Chung 1.8k 3.0× 288 0.7× 495 1.3× 300 0.8× 173 0.6× 113 2.2k
Jiliu Zhou 1.1k 1.9× 349 0.8× 374 1.0× 883 2.4× 56 0.2× 54 2.2k
Long Yu 554 0.9× 603 1.4× 234 0.6× 166 0.4× 62 0.2× 153 1.7k
Rui Huang 2.0k 3.3× 390 0.9× 322 0.8× 509 1.4× 42 0.1× 111 2.8k
Muwei Jian 1.8k 3.0× 392 0.9× 255 0.7× 412 1.1× 53 0.2× 137 2.6k
Meng-Hao Guo 1.3k 2.2× 591 1.3× 221 0.6× 382 1.0× 47 0.2× 23 2.6k
Keh-Shih Chuang 700 1.2× 273 0.6× 293 0.8× 261 0.7× 94 0.3× 24 1.3k
V. Sowmya 461 0.8× 376 0.9× 223 0.6× 299 0.8× 67 0.2× 143 1.6k
Zheng-Ning Liu 1.3k 2.2× 583 1.3× 218 0.6× 379 1.0× 44 0.2× 10 2.5k

Countries citing papers authored by Chih‐Cheng Hung

Since Specialization
Citations

This map shows the geographic impact of Chih‐Cheng Hung's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chih‐Cheng Hung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chih‐Cheng Hung more than expected).

Fields of papers citing papers by Chih‐Cheng Hung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chih‐Cheng Hung. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chih‐Cheng Hung. The network helps show where Chih‐Cheng Hung may publish in the future.

Co-authorship network of co-authors of Chih‐Cheng Hung

This figure shows the co-authorship network connecting the top 25 collaborators of Chih‐Cheng Hung. A scholar is included among the top collaborators of Chih‐Cheng Hung based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chih‐Cheng Hung. Chih‐Cheng Hung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Hu, Tianjiao, et al.. (2024). A lung nodule segmentation model based on the transformer with multiple thresholds and coordinate attention. Scientific Reports. 14(1). 31743–31743. 4 indexed citations
2.
Liu, Hong, Enmin Song, Yongde Liao, et al.. (2024). A 3D boundary-guided hybrid network with convolutions and Transformers for lung tumor segmentation in CT images. Computers in Biology and Medicine. 180. 109009–109009. 5 indexed citations
3.
Song, Enmin, Guangzhi Ma, Hong Liu, et al.. (2023). Prostate lesion segmentation based on a 3D end-to-end convolution neural network with deep multi-scale attention. Magnetic Resonance Imaging. 99. 98–109. 13 indexed citations
4.
Liu, Hong, et al.. (2023). Segmenting medical images via explicit–implicit attention aggregation. Knowledge-Based Systems. 279. 110932–110932. 8 indexed citations
5.
Song, Enmin, et al.. (2023). NMNet: Learning Multi-level semantic information from scale extension domain for improved medical image segmentation. Biomedical Signal Processing and Control. 83. 104651–104651. 8 indexed citations
6.
Song, Enmin, et al.. (2022). CFNet: A medical image segmentation method using the multi-view attention mechanism and adaptive fusion strategy. Biomedical Signal Processing and Control. 79. 104112–104112. 25 indexed citations
7.
Fang, Ming, et al.. (2022). 3 s-STNet: three-stream spatial–temporal network with appearance and skeleton information learning for action recognition. Neural Computing and Applications. 35(2). 1835–1848.
8.
Li, Lanting, et al.. (2022). Micro-expression recognition based on SqueezeNet and C3D. Multimedia Systems. 28(6). 2227–2236. 13 indexed citations
9.
Fang, Ming, et al.. (2022). A multimodal fusion model with multi-level attention mechanism for depression detection. Biomedical Signal Processing and Control. 82. 104561–104561. 79 indexed citations
10.
Fang, Ming, et al.. (2021). Mixed graph convolution and residual transformation network for skeleton-based action recognition. Applied Intelligence. 52(2). 1544–1555. 25 indexed citations
11.
Liu, Hong, Haichao Cao, Enmin Song, et al.. (2019). A cascaded dual-pathway residual network for lung nodule segmentation in CT images. Physica Medica. 63. 112–121. 70 indexed citations
12.
Cao, Haichao, Hong Liu, Chih‐Cheng Hung, et al.. (2019). Dual-branch residual network for lung nodule segmentation. Applied Soft Computing. 86. 105934–105934. 99 indexed citations
13.
Wong, M. C., et al.. (2019). A Massive Self-Organizing Map For Hyperspectral Image Classification. 1–5. 9 indexed citations
14.
Hung, Chih‐Cheng, et al.. (2012). Application of plastic containers with RFID in the marketing of fruit and vegetables in Taiwan. International journal of agricultural and biological engineering. 5(1). 35–42. 2 indexed citations
15.
Li, Cheng‐Hsuan, Wen‐Chun Huang, Bor‐Chen Kuo, & Chih‐Cheng Hung. (2008). A Novel Fuzzy Weighted C-Means Method for Image Classification. International Journal of Fuzzy Systems. 10(3). 168–173. 24 indexed citations
16.
Liu, Wenping, et al.. (2008). Hybridization of Particle Swarm Optimization with Unsupervised Clustering Algorithms for Image Segmentation. International Journal of Fuzzy Systems. 10(3). 217. 3 indexed citations
17.
Hung, Chih‐Cheng, et al.. (2006). Color and texture image segmentation using uniform local binary patterns. DigitalCommons - Kennesaw State University (Kennesaw State University). 15(3). 265–274. 5 indexed citations
18.
Hung, Chih‐Cheng, et al.. (2003). Nuclear Plume Detection and Tracking Model for the Advanced Airbornne Early Warning Surveillance Aircraft.
19.
Hung, Chih‐Cheng, et al.. (2002). An Analysis of Teacher Education Reform in Taiwan since 1944 and Its Potential Impact on the Preparation of Mathematics Teachers at the Elementary School Level.. International Journal of Educational Research. 37(2).
20.
Hung, Chih‐Cheng, et al.. (1998). A Spatial Classifier for Multispectral Data Using Contextual Information. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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