A network status evaluation method based on random projection by Jinming ZHAO

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Target Detection Label Assignment Method Based on Global Information by ZHANG Pei-pei, LU Zhen-yu

“…Aiming at this problem, this paper proposes a target detection label allocation method based on global information, which uses the assignment method to establish a global optimal label allocation mathematical model based on the loss function in the model training stage, and gives the fusion mode of the model with other object detection models, and the role played by the method in the process of object detection. …”
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A network status evaluation method based on random projection by Jinming ZHAO

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The Post-Method Teacher in the AI Age: Adapting, Collaborating, Evolving by Rosa Cecibel Varas Giler, Karina Fernanda Sotomayor

Subjects: “…ai, post-method teacher – personalize learning – digital literacy…”
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Multi-adversarial domain adaptation method based on feature correction by Yong ZHANG, Haoshuang LIU, Qi ZHANG, Wenzhe LIU

“…Domain adaptation can transfer labeled source domain information to an unlabeled but related target domain by aligning the distribution of source domain and target domain.However, most existing methods only align the low-level feature distributions of the source and target domains, failing to capture fine-grained information within the samples.To address this limitation, a feature correction-based multi-adversarial domain adaptation method was proposed.An attention mechanism to highlight transferable regions was introduced in this method and a feature correction module was deployed to align the high-level feature distributions between the two domains, further reducing domain discrepancies.Additionally, to prevent individual classifiers from overfitting their own noisy pseudo-labels,dual classifier co-training was proposed and the feature aggregation property of graph neural networks was utilized to generate more accurate source domain labels.Extensive experiments on three benchmark datasets for transfer learning demonstrate the effectiveness of the proposed method.…”
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Two-stage Detection Method for Abnormal Cluster Cervical Cells by LIANG Yi-qin, ZHAO Si-qi, WANG Hai-tao, HE Yong-jun

“…To solve this problem, we proposed a two-stage detection method for cluster cervical abnormal cells. In the first stage, we use YOLO-v5 target detection network. …”
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Review of Retargeting Methods and Assessment of Retargeted Image Objective Quality by MA Qian, DONG Wu, ZENG Qingtao, ZHANG Yan, LU Likun, ZHOU Ziyi

“…Firstly, this paper provides an overview of retargeting methods, categorizes them into content-aware image retargeting methods and those based on deep learning techniques, and analyzes the advantages and disadvantages of the two types of methods. …”
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Depression detection methods based on multimodal fusion of voice and text by Zhenrong Xu, Yuan Gao, Fang Wang, Longqian Zhang, Li Zhang, Junke Wang, Jie Shu

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A Review on Transformer-Based Methods for Human Activity Recognition by Fatemeh Sadat Lasani, Ronak Fatahi

“…In addition to investigating innovative architectures, feature extraction methods, and accuracy improvements, it also discusses the challenges and future prospects of these models in recognizing human activities. …”
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Benchmarking Anomaly Detection Methods for Extracardiac Findings in Cardiac MRI by Edgar Pinto, Patrícia M. Costa, Catarina Silva, Vitor H. Pereira, Jaime C. Fonseca, Sandro Queirós

“…Hereto, twenty state-of-the-art (SOTA) AD methods, including unsupervised, semi-supervised, and open-set supervised learning methodologies, are compared against two fully supervised baselines for detecting ECFs in anatomical planes of cardiac MR. …”
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How to Foster Inclusive Practice in Research Methods Teaching by Meredith Wilkinson, Zeynep Barlas, Jonathan Farnell, Olivier de Condappa

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Assessment of Bone Aging—A Comparison of Different Methods for Evaluating Bone Tissue by Paweł Kamiński, Aleksander Gali, Rafał Obuchowicz, Michał Strzelecki, Adam Piórkowski, Marcin Kociołek, Elżbieta Pociask, Joanna Kwiecień, Karolina Nurzyńska

“…We assessed statistical analysis, machine learning, and deep learning methods for their effectiveness in this task. …”
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Preparing educators for the digital age: teacher perceptions of active teaching methods and digital integration by Gulmira Abildinova, Elmira Abdykerimova, Almagul Assainova, Kaussar Mukhtarkyzy, Dariya Abykenova

“…IntroductionThis study investigates higher education teachers’ perceptions of active teaching methods—Case-Based Learning (CBL), Problem-Based Learning (PBL), and Team-Based Learning (TBL)—and their integration with digital technologies. …”
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Artificial Intelligence and Objective‐Function Methods Can Identify Bankfull River Channel Extents by Jonathan Garber, Karen Thompson, Matthew J. Burns, Joshphar Kunapo, Geordie Z. Zhang, Kathryn Russell

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A Method for Identifying Cervical Abnormal Cells Based on Sample Benchmark Values by ZHAO Si-qi, LIANG Yi-qin, QIN Jian, HE Yong-jun

“…The identification of cervical abnormal cells using deep learning methods usually requires a large amount of training data, but these data inevitably use different samples of cervical abnormal cells to participate in model training, and naturally miss the positive and abnormal intracellular controls of a single sample, resulting in the fact that recognition accuracy of cervical abnormal cells is not high, and the false positive rate is high. …”
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WATCHING MOVIES AND DISCOVERY LEARNING by ANA-SIMONA ILIE, PAULA MARIA BUDA, DANIELA PAHOME

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Ensemble machine learning model for forecasting wind farm generation by A. G. Rusina, Osgonbaatar Tuvshin, P. V. Matrenin, N. N. Sergeev

“…To forecast the generation of wind farms.   METHODS. This study is carried out by ensemble algorithms, such as Random Forest, AdaBoost and XGBoost, which are one of the machine learning approaches. …”
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Predicting Electromagnetic Field Exposure Using Artificial Intelligence Methods by Athanasios Manassas, Spyridon Delidimitriou, Joe Wiart, Theodoros Samaras

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Prediction Method of Lithology Log Based on XGBoost Algorithm by CHU Qingjun, GE Yunlong, TONG Maosong, WANG Yan, AN Lyuxing, YU Chuanwu, JIA Xin

“…The XGBoost algorithm has been applied in the logging field, and it provides a new method for improving the accuracy of lithology logging data.…”
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SUPPORT VECTOR MACHINE METHOD FOR PREDICTING INVESTMENT MEASURES by Olga V. Kitova, Igor B. Kolmakov, Ilya A. Penkov

“…The base features of support vector method over traditional econometric techniques for improving the forecast quality are described. …”
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