Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

“…A thorough literature evaluation is required to have a comprehensive overview of the current research on utilizing deep learning methods for email spam classification. This review aims to identify the various deep learning techniques used for email spam, their effectiveness, and areas for future research. …”
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Comparison of Machine Learning-Based Methods for Narrowband Blind Adaptive Beamforming by Shonkwiler, Lara

“…This thesis describes the performance of two machine learning-informed beamforming methods — Classification-Based Transfer Learning (CBTL) [1] and Denoising-Based Transfer Learning (DBTL). …”
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Deep learning methods to study structurally heterogeneous macromolecules in vitro and in situ by Powell, Barrett M.

“…This thesis describes the conceptualization, implementation, and application of tomoDRGN, a deep learning method developed to resolve structurally heterogeneous macromolecules in situ. …”
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Robust and efficient deep learning methods for vision-based action recognition by Xu, Yuecong

“…We observe that while VDA methods enable the learning of transferable features across domains, these methods generally assume that the video source and target domains share an identical label space. …”
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Process control of water treatment facilities using machine learning method by Tey, Shiyang

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Deep learning method for driver identification using vehicle sensor data by Chen, Youzhen

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A unified fisher’s ratio learning method for spatial filter optimization by Li, Xinyang, Guan, Cuntai, Zhang, Haihong, Ang, Kai Keng

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Entanglement in smart hydrogels: fast response time, anti-freezing and anti-drying by Feng, Yuqin, Wang, Shancheng, Li, Yaqin, Ma, Wenxia, Zhang, Gang, Yang, Ming, Li, Haibo, Yang, Yongsheng, Long, Yi

“…Different from the conventional methods which hinder the movement of the polymer network, through entanglement with HPC fibers, the composite hydrogel shows both improved Young's modulus and toughness and more importantly improved smart functionalities including response speed, anti-drying, and anti-freezing capabilities and cycle stability. …”
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Accumulated decoupled learning with gradient staleness mitigation for convolutional neural networks by Zhuang, Huiping, Weng, Zhenyu, Luo, Fulin, Toh, Kar-Ann, Li, Haizhou, Lin, Zhiping

“…In addition, our ADL is shown to have the fastest training speed among the compared methods. The code will be ready soon in https://github.com/ZHUANGHP/Accumulated- Decoupled-Learning.git.…”
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Sustainable oil palm resource assessment based on an enhanced deep learning method by Liu, Xinni, Kamarul Hawari, Ghazali, Shah, Akeel A.

“…The enhanced FRCNN (EFRCNN) leads to improved performance for detecting objects (in the same image) when they are of multiple sizes by using a feature concatenation method. Transfer learning based on a ResNet50 model is used to extract the features of the input image. …”
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Recent Progress of Deep Learning Methods for Health Monitoring of Lithium-Ion Batteries by Madani, Seyed Saeed, Ziebert, Carlos, Vahdatkhah, Parisa, Sadrnezhaad, Sayed Khatiboleslam

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Predicting the work function of 2D MXenes using machine-learning methods by Roy, Pranav, Rekhi, Lavie, Koh, See Wee, Li, Hong, Choksi, Tej S.

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Deep learning methods for genome-based prediction of drug resistance in Mycobacterium tuberculosis by Wang, C

“…In this doctoral thesis, which is based on the CRyPTIC datasets, we explore and develop a variety of machine learning and deep learning methods. Our research includes the application of binary classifiers for predicting MTB resistance labels, the employment of multi-class classification and ordinal regression techniques for predicting minimum inhibitory concentrations of MTB, and the implementation of calibration models to improve the uncertainty estimation in our predictions.…”

E-Module in TVET: unveiling brazing and riveting methods through VAK learning by Hashim, Suhaizal, Mohamad Ali, Nur Alianni, Masran, Saiful Hadi

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Robust deep learning methods for accountable contrast-agent-free CMR imaging in clinical applications by Gonzales, RA

“…</p> <br> <p>The first goal of this thesis is to provide motion-corrected T1 maps by developing a deep learning-based method for correcting motion artefacts. …”

A special section on methods and application in biomedical imaging – part 1 by Deniz, Luis Gomez, Ng, Eddie Yin Kwee

“…This special section on Methods and Application in Biomedical Imaging presents the ongoing and active research in the Biomedical Imaging area, with emphasis on machine learning and image processing state-of-the art techniques. …”
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MCI-frcnn: a deep learning method for topological micro-domain boundary detection by Tian, Simon Zhongyuan, Yin, Pengfei, Jing, Kai, Yang, Yang, Xu, Yewen, Huang, Guangyu, Ning, Duo, Fullwood, Melissa Jane, Zheng, Meizhen

“…In all, the MCI-frcnn deep learning method which we developed in this work is a general tool for micro-domain boundary detection.…”
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Multimodal fusion for navigation of autonomous mobile robots using a deep learning method by Lee, Anthony Wen Hao

“…Many studies have been done to explore new approaches such as using advanced sensor technologies and machine learning algorithms, which aims to improve the accuracy and efficiency of these collision-avoidance methods for robots. …”
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Academic achievement inspired machine learning methods for student grade prediction and at-risk detection by Wei, Qiu

“…Grade prediction is one of the several sub-disciplines among learning analytics transcends and has received increasing attention in recent years and remains one of the most challenging tasks. …”
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A joint learning method with consistency-aware for low-resolution facial expression recognition by Xie, Yuanlun, Tian, Wenhong, Song, Liang, Xue, Ruini, Zha, Zhiyuan, Wen, Bihan

“…Existing facial expression recognition (FER) methods are mainly devoted to learning discriminative features from high-resolution images. …”
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