Browsing NTNU Open by Author "Yang, Zhirong"
Now showing items 1-20 of 26
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A 91-Channel Hyperspectral LiDAR for Coal/Rock Classification
Shao, Hui; Chen, Yuwei; Yang, Zhirong; Jiang, Changhui; Li, Wei; Wu, Haobo; Wen, Zhijie; Wang, Shaowei; Puttnon, Eetu; Hyyppä, Juha (Journal article; Peer reviewed, 2019)During the mining operation, it is a critical task in coal mines to significantly improve the safety by precision coal mining sorting and rock classification from different layers. It implies that a technique for rapidly ... -
An intelligent decision-making process for hydro scheduling.
Babayev, Piri (Master thesis, 2022)In Norway hydropower plants are the leading source of electricity production - around 90% of all of the electricity produced. These hydropower plants are built around water reservoirs that generate energy by releasing the ... -
Analysis of the effect of indoor environment on pupils’ health in one Norwegian school during COVID-19 pandemic
Ulvestad, Anita; Cao, Guangyu; Gustavsen, Kai; Vogt, Matthias; Rismyhr, Tore; Yang, Zhirong (Chapter, 2021)The aim of this project is to investigate and predict the quantified effect of indoor environment on pupils’ health in schools in Norway during the COVID-19 pandemic. The results are based on field measurements of the ... -
Application of machine learning to ILI data denoising
Dahl, Sondre Strande; Larsen, Erik Stensrud (Master thesis, 2021)Dette prosjektet har som mål å anvende maskinlæring i filtreringsprosessen av data fra inline-inspeksjon (ILI) av olje- og gassrørledninger. Rørledningen er utsatt for korrosjon, både innvendig og utvendig. Konsekvensene ... -
Application of machine learning to ILI datadenoising
Dahl, Sondre Strande; Larsen, Erik Stensrud (Master thesis, 2021)Dette prosjektet har som mål å anvende maskinlæring i filtreringsprosessen av data fra inline-inspeksjon (ILI) av olje- og gassrørledninger. Rørledningen er utsatt for korrosjon, både innvendig og utvendig. Konsekvensene ... -
ASSIST: Accuracy-driven Sampling Strategies for Improved Supervised Training
Smedås, Halvor Bakken (Master thesis, 2021)Hvordan vi bruker treningstid har blitt viktigere med nevrale nettverkets stadig mer komplekse arkitekturer. Nyere forskning presenterer strategiske datautvelgingsmetoder som et alternativ til mini-batch SGD, som forenkler ... -
ChromosomeNet: A massive dataset enabling benchmarking and building basedlines of clinical chromosome classification
Lin, Chengchuang; Chen, Hanbiao; Huang, Jiesheng; Peng, Jing; Guo, Li; Yang, Zhirong; Du, Jiahua; Li, Shuangyin; Yin, Aihua; Zhao, Gansen (Journal article; Peer reviewed, 2022)Chromosome karyotyping analysis is a vital cytogenetics technique for diagnosing genetic and congenital malformations, analyzing gestational and implantation failures, etc. Since the chromosome classification as an essential ... -
CIR-Net: Automatic Classification of Human Chromosome based on Inception-ResNet Architecture
Lin, Chenguang; Zhao, Gansen; Yang, Zhirong; Yin, Aihua; Wang, Xinming; Guo, Li; Chen, Hanbiao; Ma, Zhaohui; Zhao, Lei; Luo, Haoyu; Wang, Tianxing; Ding, Bichao; Pang, Xiongwen; Chen, Qiren (Peer reviewed; Journal article, 2020)Method: This paper focuses on chromosome classification because it is critical for chromosome karyotyping. In recent years, deep learning-based methods are the most promising methods for solving the tasks of chromosome ... -
Classification of long sequential data using circular dilated convolutional neural networks
Cheng, Lei; Khalitov, Ruslan; Yu, Tong; Zhang, Jing; Yang, Zhirong (Peer reviewed; Journal article, 2023)Classification of long sequential data is an important Machine Learning task and appears in many application scenarios. Recurrent Neural Networks, Transformers, and Convolutional Neural Networks are three major techniques ... -
Distribution and gradient constrained embedding model for zero-shot learning with fewer seen samples
Zhang, Jing; Geng, YangLi-ao; Wang, Wen; Sun, Wenju; Yang, Zhirong; Li, Qingyong (Peer reviewed; Journal article, 2022)Zero-Shot Learning (ZSL), which aims to recognize unseen classes with no training data, has made great progress in recent years. However, established ZSL methods implicitly assumed that there exist sufficient labeled samples ... -
Doubly Stochastic Neighbor Embedding on Spheres
Lu, Yao; Corander, Jukka; Yang, Zhirong (Journal article; Peer reviewed, 2019)Stochastic Neighbor Embedding (SNE) methods minimize the divergence between the similarity matrix of a high-dimensional data set and its counterpart from a low-dimensional embedding, leading to widely applied tools for ... -
Downhole working conditions analysis and drilling complications detection method based on deep learning
Wang, Chao; Liu, Gonghui; Yang, Zhirong; Li, Jun; Zhang, Tao; Jiang, Hailong; Cao, Chenguang (Peer reviewed; Journal article, 2020)Drilling complications, which are usually hard to be discovered in time using the traditional surface detecting methods, result in much time and money wasted in handling these problems. Restricted to data transmission speed ... -
Feasibility Study on Hyperspectral LiDAR for Ancient Huizhou-Style Architecture Preservation
Shao, Hui; Chen, Yuwei; Yang, Zhirong; Jiang, Changhui; Li, Wei; Wu, Haohao; Wang, Shaowei; Yang, Fan; Chen, Jie; Puttnon, Eetu; Hyyppä, Juha (Journal article; Peer reviewed, 2020)Huizhou-style ancient architecture was one of the most important genres of architectural heritage in China. The architecture employed bricks, woods, and stones as raw materials, and timber frames were significant structures. ... -
Learning Image Relations with Contrast Association Networks
Lu, Yao; Yang, Zhirong; Kannala, Juho; Kaski, Samuel (Chapter, 2019)Inferring the relations between two images is an important class of tasks in computer vision. Examples of such tasks include computing optical flow and stereo disparity. We treat the relation inference tasks as a machine ... -
Machine Learning for Hydropower Scheduling: State of the Art and Future Research Directions
Bordin, Chiara; Skjelbred, Hans Ivar; Kong, Jiehong; Yang, Zhirong (Peer reviewed; Journal article, 2020)This paper investigates and discusses the current and future role of machine learning (ML) within the hydropower sector. An overview of the main applications of ML in the field of hydropower operations is presented to show ... -
Mandrake: visualizing microbial population structure by embedding millions of genomes into a low-dimensional representation
Lees, John A.; Tonkin-Hill, Gerry; Yang, Zhirong; Corander, Jukka (Journal article; Peer reviewed, 2022) -
Non-uniform Temperature Distribution's Impact on Downhole Weight on Bit Measurement (DWOB) and the Novel Compensatory Method
Wang, Chao; Liu, Gonghui; Li, Jun; Zhang, Tao; Yang, Zhirong; Jiang, Hailong; Ren, Kai; Wu, Zhe (Peer reviewed; Journal article, 2020)Non-uniform temperature distribution of DWOB measuring devices has a great effect on the accuracies of weight on bit (WOB) readings. To study the influence, two types of non-uniform temperature distributions of the WOB ... -
Paramixer: Parameterizing Mixing Links in Sparse Factors Works Better than Dot-Product Self-Attention
Yu, Tong; Khalitov, Ruslan; Cheng, Lei; Yang, Zhirong (Journal article, 2022)Self-Attention is a widely used building block in neural modeling to mix long-range data elements. Most self-attention neural networks employ pairwise dot-products to specify the attention coefficients. However, these ... -
Self-Supervised Machine Learning for DNA sequences
Ravaghi, Mahdi (Master thesis, 2023)Denne oppgåva utforskar bruken av sjølv-rettleia maskinlæring på genomdata og vurderer korleis det påverkar ytelsen til nedstraums ’fine-tuning’ oppgåver. Studien bygger på tidlegare forsking gjort på skalérbare nevrale ... -
A Simple and Novel Method to Predict the Hospital Energy Use Based on Machine Learning: A Case Study in Norway
Xue, Kai; Ding, Yiyu; Yang, Zhirong; Nord, Natasa; Barillec, Mael Roger Albert; Mathisen, Hans Martin; Liu, Meng; Giske, Tor Emil; Stenstad, Liv-Inger; Cao, Guangyu (Peer reviewed; Journal article, 2020)Hospitals are one of the most energy-consuming commercial buildings in many countries as a highly complex organization because of a continuous energy utilization and great variability of usage characteristic. With the ...