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Lianjie Wang

dblp:18/2688 · DBLP profile ↗
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4ranked-venue papers
0as first author
2since 2021 · last 2026
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2Systems, architecture and hardware · 1 · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-AI interaction · 100%
Artificial intelligence
1 paper
Segmentation and scene understanding · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › Segmentation and scene understanding
interactive segmentation		 0.412020
Human-in-the-loop image segmentation and annotation · Sci. China Inf. Sci. 2020
Human-AI interaction › interactive machine learning
interactive segmentation		 0.412020
Human-in-the-loop image segmentation and annotation · Sci. China Inf. Sci. 2020
Human-AI interaction
human-in-the-loop		 0.112020
Human-in-the-loop image segmentation and annotation · Sci. China Inf. Sci. 2020
YearPublicationVenuePosition
2026 Optimal neutron spectrum dataset for medical isotopes production
Qingquan Pan, Lianjie Wang, Bangyang Xia
 Adv. Eng. Informatics2
2025 Pocket convolution Mamba for brain tumor segmentation
Hao Zhang 0068, Yunhao Zhao, Lianjie Wang, Wenyin Zhang, Yeh-Cheng Chen, Naixue Xiong
 J. Supercomput.4
2020 Human-in-the-loop image segmentation and annotation
Lianjie Wang, Jin Xie 0001, Pengfei Zhu 0001
 Sci. China Inf. Sci.2
2005 Information theory-based algorithm for in silico prediction of PCR products with whole genomic sequences as templates
abstract
BACKGROUND: A new algorithm for assessing similarity between primer and template has been developed based on the hypothesis that annealing of primer to template is an information transfer process. RESULTS: Primer sequence is converted to a vector of the full potential hydrogen numbers (3 for G or C, 2 for A or T), while template sequence is converted to a vector of the actual hydrogen bond numbers formed after primer annealing. The former is considered as source information and the latter destination information. An information coefficient is calculated as a measure for fidelity of this information transfer process and thus a measure of similarity between primer and potential annealing site on template. CONCLUSION: Successful prediction of PCR products from whole genomic sequences with a computer program based on the algorithm demonstrated the potential of this new algorithm in areas like in silico PCR and gene finding.
Youfang Cao, Lianjie Wang, Kexue Xu, Chunhai Kou, Gavin Yulei Zhang, Guifang Wei, Junjian He, Yunfang Wang, Liping Zhao 0003
 BMC Bioinform.2