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Full-Text Articles in Engineering
Deep Gabor Neural Network For Automatic Detection Of Mine-Like Objects In Sonar Imagery, Hoang Thanh Le, Son Lam Phung, Philip B. Chapple, Abdesselam Bouzerdoum, Christian H. Ritz, Le Chung Tran
Deep Gabor Neural Network For Automatic Detection Of Mine-Like Objects In Sonar Imagery, Hoang Thanh Le, Son Lam Phung, Philip B. Chapple, Abdesselam Bouzerdoum, Christian H. Ritz, Le Chung Tran
Faculty of Engineering and Information Sciences - Papers: Part B
With the advances in sonar imaging technology, sonar imagery has increasingly been used for oceanographic studies in civilian and military applications. High-resolution imaging sonars can be mounted on various survey platforms, typically autonomous underwater vehicles, which provide enhanced speed and improved data quality with long-range support. This paper addresses the automatic detection of mine-like objects using sonar images. The proposed Gabor-based detector is designed as a feature pyramid network with a small number of trainable weights. Our approach combines both semantically weak and strong features to handle mine-like objects at multiple scales effectively. For feature extraction, we introduce a parameterized …
A Novel Monte Carlo-Based Neural Network Model For Electricity Load Forecasting, Binbin Yong, Zijian Xu, Jun Shen, Huaming Chen, Jianqing Wu, Fucun Li, Qingguo Zhou
A Novel Monte Carlo-Based Neural Network Model For Electricity Load Forecasting, Binbin Yong, Zijian Xu, Jun Shen, Huaming Chen, Jianqing Wu, Fucun Li, Qingguo Zhou
Faculty of Engineering and Information Sciences - Papers: Part B
The ongoing rapid growth of electricity over the past few decades greatly promotes the necessity of accurate electricity load forecasting. However, despite a great number of studies, electricity load forecasting is still an enormous challenge for its complexity. Recently, the developments of machine learning technologies in different research areas have demonstrated its great advantages. General Vector Machine (GVM) is a new machine learning model, which has been proven very effective in time series prediction. In this article, we firstly review the basic concepts and implementation of GVM. Then we apply it in electricity load forecasting, which is based on the …
Attention-Based Knowledge Tracing With Heterogeneous Information Network Embedding, Nan Zhang, Ye Du, Ke Deng, Li Li, Jun Shen, Geng Sun
Attention-Based Knowledge Tracing With Heterogeneous Information Network Embedding, Nan Zhang, Ye Du, Ke Deng, Li Li, Jun Shen, Geng Sun
Faculty of Engineering and Information Sciences - Papers: Part B
Knowledge tracing is a key area of research contributing to personalized education. In recent times, deep knowledge tracing has achieved great success. However, the sparsity of students’ practice data still limits the performance and application of knowledge tracing. An additional complication is that the contribution of the answer record to the current knowledge state is different at each time step. To solve these problems, we propose Attention-based Knowledge Tracing with Heterogeneous Information Network Embedding (AKTHE). First, we describe questions and their attributes with a heterogeneous information network and generate meaningful node embeddings. Second, we capture the relevance of historical data …