Search Results for author: Wenli Yang

Found 7 papers, 0 papers with code

Impact and influence of modern AI in metadata management

no code implementations28 Jan 2025 Wenli Yang, Rui Fu, Muhammad Bilal Amin, Byeong Kang

Metadata management plays a critical role in data governance, resource discovery, and decision-making in the data-driven era.

Decision Making Management

Advancing Oyster Phenotype Segmentation with Multi-Network Ensemble and Multi-Scale mechanism

no code implementations20 Jan 2025 Wenli Yang, Yanyu Chen, Andrew Trotter, Byeong Kang

Phenotype segmentation is pivotal in analysing visual features of living organisms, enhancing our understanding of their characteristics.

Instance Segmentation Segmentation +1

A Comprehensive Survey on Integrating Large Language Models with Knowledge-Based Methods

no code implementations19 Jan 2025 Wenli Yang, Lilian Some, Michael Bain, Byeong Kang

This approach aims to combine the generative language understanding of LLMs and the precise knowledge representation systems by which they are integrated.

Proceedings of Principle and practice of data and Knowledge Acquisition Workshop 2022 (PKAW 2022)

no code implementations7 Nov 2022 Qing Liu, Wenli Yang, Shiqing Wu

Over the past two decades, PKAW has provided a forum for researchers and practitioners to discuss the state-of-the-arts in the area of knowledge acquisition and machine intelligence (MI, also Artificial Intelligence, AI).

Hybrid CNN -Interpreter: Interpret local and global contexts for CNN-based Models

no code implementations31 Oct 2022 Wenli Yang, Guan Huang, Renjie Li, Jiahao Yu, Yanyu Chen, Quan Bai, Beyong Kang

Convolutional neural network (CNN) models have seen advanced improvements in performance in various domains, but lack of interpretability is a major barrier to assurance and regulation during operation for acceptance and deployment of AI-assisted applications.

Feature Correlation

A Comprehensive Review on Deep Supervision: Theories and Applications

no code implementations6 Jul 2022 Renjie Li, Xinyi Wang, Guan Huang, Wenli Yang, Kaining Zhang, Xiaotong Gu, Son N. Tran, Saurabh Garg, Jane Alty, Quan Bai

Deep supervision, or known as 'intermediate supervision' or 'auxiliary supervision', is to add supervision at hidden layers of a neural network.

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