Jianxiong Gao,Yi Cheng,Jianwei Gao
Jianxiong Gao
Predicting the outcomes of sports events is inherently difficult due to the unpredictable nature of gameplay and the complex interplay of numerous influencing factors. In this study, we present a deep learning framework that combines a one-...
A path aggregation network with deformable convolution for visual object detection [0.03%]
一种基于可形变卷积的路径聚合网络用于视觉目标检测方法
Chengming Rao,Zunhao Hu,QiMing Zhao et al.
Chengming Rao et al.
One of the main challenges encountered in visual object detection is the multi-scale issue. Many approaches have been proposed to tackle this issue. In this article, we propose a novel neck that can perform effective fusion of multi-scale f...
Keshav Sharma,Jyoti Arora,Pooja Kherwa et al.
Keshav Sharma et al.
Class imbalance is a prevalent challenge in image classification tasks, where certain classes are significantly underrepresented compared to others. This imbalance often leads to biased models that perform poorly in predicting minority clas...
Improving course evaluation processes in higher education institutions: a modular system approach [0.03%]
高等学校课程评价过程的改进：模块系统方法
İlker Kocaoğlu,Erinç Karataş
İlker Kocaoğlu
Course and instructor evaluations (CIE) are essential tools for assessing educational quality in higher education. However, traditional CIE systems often suffer from inconsistencies between structured responses and open-ended feedback, lead...
Xiaohui Dong,Xinyu Zhang,Zhengluo Li et al.
Xiaohui Dong et al.
As a key natural language processing (NLP) task, question generation (QG) is crucial for boosting educational quality and fostering personalized learning. This article offers an in-depth review of the research advancements and future direct...
Data trace as the scientific foundation for trusted metrological data: a review for future metrology direction [0.03%]
数据溯源是可信计量数据的科学基础——面向未来计量方向的评论文章
Zhanshuo Cao,Boyong Gao,Zilong Liu et al.
Zhanshuo Cao et al.
In the context of the digital transformation of metrology, ensuring the trustworthiness and integrity of measurement data during its generation, transmission, and storage-i.e., trustworthy detection of measurement data-has become a critical...
A new machine learning method for rainfall classification: temporal random tree [0.03%]
一种新的降雨分类机器学习方法：时序随机树
Kokten Ulas Birant,Bita Ghasemkhani,Özlem Varlıklar et al.
Kokten Ulas Birant et al.
Traditional classification algorithms usually assume that all samples in a dataset contribute equally to the training of a machine learning model, which is not always the case. In fact, samples in temporal data, such as precipitation data, ...
Effective classification for neonatal brain injury using EEG feature selection based on elastic net regression and improved crow search algorithm [0.03%]
基于弹性网回归和改进型 Crow 搜索算法的新生儿脑损伤分类方法研究
Ling Li,Tao Yue,Hui Wu et al.
Ling Li et al.
Neonatal brain injury carries the risk of neurological sequelae such as epileptic seizures, cerebral palsy, intellectual disability, and even death. Classification methods based on electroencephalography (EEG) signals and machine learning a...
Jeongseon Kim,Soohwan Jeong,Jungeun Kim et al.
Jeongseon Kim et al.
In social network analysis, bridges play a critical role in maintaining connectivity and facilitating the dissemination of information between communities. Despite increasing interest in bridge structures, a systematic classification of the...
DDSUD: dynamically detecting subsequence uncertainty and diversity for active learning in imbalanced Chinese sentiment analysis [0.03%]
基于不平衡数据的中文情感分析中的主动学习子序列不确定性与多样性的动态检测算法
Shufeng Xiong,Yibo Si,Guipei Zhang et al.
Shufeng Xiong et al.
Sentiment structure analysis in Chinese text typically relies on supervised deep-learning methods for sequence labeling. However, obtaining large-scale labeled datasets is both resource-intensive and time-consuming. To address these challen...