Learning Power Systems Waveform Incipient Patterns Through Few-Shot Meta-Learning by Lixian Shi, Qiushi Cui, Yang Weng, Yigong Zhang, Shilong Chen, Jian Li, Wenyuan Li

“…To resolve these problems, a few-shot meta-learning framework for incipient fault detection (FSMLF-IFD) is proposed in this paper. …”
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Correction: Correction: A neural network model for online one-shot storage of pattern sequences. by PLOS One Staff

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One-Shot M-Array Pattern Based on Coded Structured Light for Three-Dimensional Object Reconstruction by Xiaojun Jia, Zihao Liu

“…A robust pattern decoding method for reconstructing objects from a one-shot pattern is then proposed. …”
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Zero-Shot Classification of Art With Large Language Models by Tatsuya Tojima, Mitsuo Yoshida

“…In this study, we propose the zero-shot classification method to perform automatic annotation in data processing for art price prediction by leveraging large language models (LLMs). …”
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Loss Architecture Search for Few-Shot Object Recognition by Jun Yue, Zelang Miao, Yueguang He, Nianchun Du

“…We conduct experiments on three popular datasets for few-shot learning. The results show that the proposed approach achieves better performance than state-of-the-art methods.…”
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Zero-shot reranking with dense encoder models for news background linking by Marwa Essam, Tamer Elsayed

“…In this paper, we investigate multiple methods to integrate both the lexical and semantic relevance signals for better reranking of candidate background links. To represent news articles in the semantic space, we compare multiple Transformer-based encoder models in a zero-shot setting without the need for any labeled data. …”
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Learning under label noise through few-shot human-in-the-loop refinement by Aaqib Saeed, Dimitris Spathis, Jungwoo Oh, Edward Choi, Ali Etemad

“…Finally, it achieves better generalizability and robustness by merging the seed and fine-tuned models via weighted parameter averaging. …”
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Substitute locations of urban spaces in films shot in Spain: motivations, representations and consequences by Víctor Aertsen, Carlos Manuel Valdés, Antonio Martínez Puche

“…Through these different sections, we seek to contribute to a better understanding of the motivations, representations and geographical and economic consequences of this filmic practice. …”
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Positional embeddings and zero-shot learning using BERT for molecular-property prediction by Medard Edmund Mswahili, JunHa Hwang, Jagath C. Rajapakse, Kyuri Jo, Young-Seob Jeong

“…It also explores zero-shot learning analysis and the model’s performance on various classification and regression tasks. …”
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Predicting correlation relationships of entities between attack patterns and techniques based on word embedding and graph convolutional network by Weicheng QIU, Xiuzhen CHEN, Yinghua MA, Jin MA, Zhihong ZHOU

“…Threat analysis relies on knowledge bases that contain a large number of security entities.The scope and impact of security threats and risks are evaluated by modeling threat sources, attack capabilities, attack motivations, and threat paths, taking into consideration the vulnerability of assets in the system and the security measures implemented.However, the lack of entity relations between these knowledge bases hinders the security event tracking and attack path generation.To complement entity relations between CAPEC and ATT＆amp;CK techniques and enrich threat paths, an entity correlation prediction method called WGS was proposed, in which entity descriptions were analyzed based on word embedding and a graph convolution network.A Word2Vec model was trained in the proposed method for security domain to extract domain-specific semantic features and a GCN model to capture the co-occurrence between words and sentences in entity descriptions.The relationship between entities was predicted by a Siamese network that combines these two features.The inclusion of external semantic information helped address the few-shot learning problem caused by limited entity relations in the existing knowledge base.Additionally, dynamic negative sampling and regularization was applied in model training.Experiments conducted on CAPEC and ATT＆amp;CK database provided by MITRE demonstrate that WGS effectively separates related entity pairs from irrelevant ones in the sample space and accurately predicts new entity relations.The proposed method achieves higher prediction accuracy in few-shot learning and requires shorter training time and less computing resources compared to the Bert-based text similarity prediction models.It proves that word embedding and graph convolutional network based entity relation prediction method can extract new entity correlation relationships between attack patterns and techniques.This helps to abstract attack techniques and tactics from low-level vulnerabilities and weaknesses in security threat analysis.…”
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Tongue-LiteSAM: A Lightweight Model for Tongue Image Segmentation With Zero-Shot by Daiqing Tan, Hao Zang, Xinyue Zhang, Han Gao, Ji Wang, Zaijian Wang, Xing Zhai, Huixia Li, Yan Tang, Aiqing Han

“…Conclusion: The Tongue-LiteSAM model provides a more objective and consistent solution for tongue diagnosis, and has better zero-shot segmentation capabilities. By optimizing the model structure and data processing strategies, the accuracy and practicality of tongue diagnosis models are effectively improved, offering new technical support for the modernization and precision of TCM tongue diagnosis.…”
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A robust adaptive meta-sample generation method for few-shot time series prediction by Chao Zhang, Defu Jiang, Kanghui Jiang, Jialin Yang, Yan Han, Ling Zhu, Libo Tao

“…Compared with the benchmark methods, the prediction model combined with JLSG-Diffusion shows better accuracy.…”
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Influence of the surface roughness, lubrication and grinding on tribological properties of the c35 steel shot-peened surfaces by Martin Vicen, Otakar Bokůvka, Libor Trško, Richard Joch, Jozef Bronček, Ružica Nikolić, Robert Ulewicz

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Multilevel support-assisted prototype optimization network for few-shot medical segmentation of lung lesions by Yuan Tian, Yongquan Liang, Yufeng Chen, Jingjing Zhang, Hongyang Bian

“…Abstract Medical image annotation is scarce and costly. Few-shot segmentation has been widely used in medical image from only a few annotated examples. …”
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Examining transaction-specific satisfaction and trust in Airbnb and hotels. An application of BERTopic and Zero-shot text classification by Manuel Rey-Moreno, Manuel Jesús Sánchez-Franco, María De la Sierra Rey-Tienda

“…Secondly, our analysis applies a Zero-shot classification approach for classifying guest reviews into labels related to guests' satisfaction and trust. …”
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PLZero: placeholder based approach to generalized zero-shot learning for multi-label recognition in chest radiographs by Chengrong Yang, Qiwen Jin, Fei Du, Jing Guo, Yujue Zhou

“…Abstract By leveraging large-scale image-text paired data for pre-training, the model can efficiently learn the alignment between images and text, significantly advancing the development of zero-shot learning (ZSL) in the field of intelligent medical image analysis. …”
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Enhancing zero-shot relation extraction with a dual contrastive learning framework and a cross-attention module by Diyou Li, Lijuan Zhang, Jie Huang, Neal Xiong, Lei Zhang, Jian Wan

“…Abstract Zero-shot relation extraction (ZSRE) is essential for improving the understanding of natural language relations and enhancing the accuracy and efficiency of natural language processing methods in practical applications. …”
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EMNet: A Novel Few-Shot Image Classification Model with Enhanced Self-Correlation Attention and Multi-Branch Joint Module by Fufang Li, Weixiang Zhang, Yi Shang

“…Experimental results show that our model performs better than existing models in one-shot and five-shot tasks on mini-ImageNet, CUB-200, and CIFAR-FS datasets, which proves the proposed model to be an efficient end-to-end solution for few-shot image classification. …”
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Performance, Test-retest Reliability, and Measurement Error of the Upper Limb Seated Shot Put Test According to Different Positions of Execution by Gustavo O Tagliarini, José R. de S Junior, Glauber M, P Barbosa, Leonardo L B Secchi

“…# BACKGROUND The unilateral Seated Shot-Put Test (USSPT) is an easy to apply, inexpensive tool that can be used to assess shoulder performance unilaterally. …”
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Finite Element Analysis of Effect of Double Shot Peening on Residual Stresses of 18CrNiMo7-6 Gear Steel by Wang Zhen, Sun Hao, Wang Guohao

“…Through variance analysis, when the shot peening coverage is 100%, the second shot peening strengthening is carried out by using the processing parameters with smaller shot peening intensity,which has a better improvement effect on the uniformity of surface layer residual compressive stress, and the uniformity of surface residual compressive stress is increased by 28.76%.…”
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