Thermal conductivity evaluation of magnetized non-Newtonian nanofluid and dusty particles with thermal radiation by Hussain Syed Modassir, Khan Umair, Obalalu Adebowale Martins, Zaib Aurang

Get full text

Local Diversity-Guided Weakly Supervised Fine-Grained Image Classification Method by Yuebo Meng, Xianglong Luo, Hua Zhan, Bo Wang, Shilong Su, Guanghui Liu

“…Extensive experiments conducted on four fine-grained datasets and explainable visualization demonstrate that the LDGNet can effectively enhance discriminative region localization and detailed feature acquisition for fine-grained objects, achieving competitive performance over other state-of-the-art algorithms.…”
Get full text

A Real-Time DAO-YOLO Model for Electric Power Operation Violation Recognition by Xiaoliang Qian, Yang Li, Xinyu Ding, Longxiang Luo, Jinchao Guo, Wei Wang, Peixu Xing

“…Finally, a novel dataset named EPOVR-v1.0 is proposed to evaluate the performance of the object detection model applied in EPOVR. …”
Get full text

Joint Intensity and Spatio-Temporal Representation Learning for Extreme Precipitation Nowcasting by Zefeng Pan, Renlong Hang, Qingshan Liu, Chunxiang Shi, Zhiqiang Xu, Xiao-Tong Yuan

“…However, the existing methods tend to inadequately weigh precipitation intensity features by only implicitly learning and modeling these features within the spatial distribution. …”
Get full text

A Novel SHiP Vector Machine for Network Intrusion Detection by Sowmya T., E. A. Mary Anita

“…In this paper, network intrusion detection is proposed using an improved version of the support vector machine model to detect DoS attacks. Here, the SVM model considers the weight parameter along with the kernel to find the best decision boundary that separates the data into DoS and normal. …”
Get full text

Cloud-Based Intrusion Detection Approach Using Machine Learning Techniques by Hanaa Attou, Azidine Guezzaz, Said Benkirane, Mourade Azrour, Yousef Farhaoui

“…This paper presents a cloud-based intrusion detection model based on random forest (RF) and feature engineering. …”
Get full text

Prediction method of gas emission in working face based on feature selection and BO-GBDT by MA Wenwei

“…In fact, redundant or irrelevant features reduced the model's prediction accuracy. To further improve performance, five hyperparameter optimization algorithms were applied to the GBDT model. …”
Get full text

A Lightweight Pavement Defect Detection Algorithm Integrating Perception Enhancement and Feature Optimization by Xiang Zhang, Xiaopeng Wang, Zhuorang Yang

“…To address the current issue of large computations and the difficulty in balancing model complexity and detection accuracy in pavement defect detection models, a lightweight pavement defect detection algorithm, PGS-YOLO, is proposed based on YOLOv8, which integrates perception enhancement and feature optimization. …”
Get full text

Enhanced ResNet-50 for garbage classification: Feature fusion and depth-separable convolutions. by Lingbo Li, Runpu Wang, Miaojie Zou, Fusen Guo, Yuheng Ren

“…Specifically, first, a redundancy-weighted feature fusion module is proposed, enabling the model to fully leverage valuable feature information, thereby improving its performance. …”
Get full text

Optimizing unsupervised feature engineering and classification pipelines for differentiated thyroid cancer recurrence prediction by Emmanuel Onah, Uche Jude Eze, Abdullahi Salahudeen Abdulraheem, Ugochukwu Gabriel Ezigbo, Kosisochi Chinwendu Amorha, Fidele Ntie-Kang

“…This study aimed to enhance predictive performance by refining feature engineering and evaluating a diverse ensemble of machine learning models using the UCI DTC dataset. …”
Get full text

What Matters in Irony Detection: An Extended Feature Engineering for Irony Detection in English Tweets. by Linrui Zhang, Qixiang Pang, Belinda Copus

“…The primary research approach has focused on selecting the most appropriate language model for specific NLP tasks and then incorporating linguistic features to enhance the model’s performance. …”
Get full text

Network intrusion detection method based on VAE-CWGAN and fusion of statistical importance of feature by Taotao LIU, Yu FU, Kun WANG, Xueyuan DUAN

“…Considering the problems of traditional intrusion detection methods limited by the class imbalance of datasets and the poor representation of selected features, a detection method based on VAE-CWGAN and fusion of statistical importance of features was proposed.Firstly, data preprocessing was conducted to enhance data quality.Secondly, a VAE-CWGAN model was constructed to generate new samples, addressing the problem of imbalanced datasets, ensuring that the classification model no longer biased towards the majority class.Next, standard deviation, difference of median and mean were used to rank the features and fusion their statistical importance for feature selection, aiming to obtain more representative features, which made the model can better learn data information.Finally, the mixed data set after feature selection was classified through a one-dimensional convolutional neural network.Experimental results show that the proposed method demonstrates good performance advantages on three datasets, namely NSL-KDD, UNSW-NB15, and CIC-IDS-2017.The accuracy rates are 98.95%, 96.24%, and 99.92%, respectively, effectively improving the performance of intrusion detection.…”
Get full text

Enhancing multiclass brain tumor diagnosis using SVM and innovative feature extraction techniques by Mustafa Basthikodi, M. Chaithrashree, B. M. Ahamed Shafeeq, Ananth Prabhu Gurpur

“…Further performance gains were realized by applying feature extraction techniques—HOG and LBP—in conjunction with SVM, resulting in an acc_val of 95.95%. …”
Get full text

Integrating CT-based radiomics and clinical features to better predict the prognosis of acute pancreatitis by Hang Chen, Yao Wen, Xinya Li, Xia Li, Liping Su, Xinglan Wang, Fang Wang, Dan Liu

“…Abstract Objectives To develop and validate the performance of CT-based radiomics models for predicting the prognosis of acute pancreatitis. …”
Get full text

Life Prediction Method of Remanufactured Machinery Equipment Based on Vibration Signal Feature Extraction by Bin Li, Le Kui, Jingdong Luo, Shiyong Chen

“…After that, the value extracted from the vibration signal of the double-row roller equipment is used as the degradation feature. In order to reduce the influence of irregular characteristics in the vibration signal and simplify the complexity of the vibration signal, the wavelet transform and the support vector machine model are combined, according to the degradation after decomposition. …”
Get full text

Non-destructive Identification of Moldy Walnuts by Fusing X-Ray and Visual Image Features by NING Xinyue, ZHANG Hui, JI Shuai, LAI Lisi

“…The experimental results showed that the ELM model developed using SPA optimized feature set had the best performance. …”
Get full text

Risk stratification of thymic epithelial tumors based on peritumor CT radiomics and semantic features by Lin Zhang, Zhihan Xu, Yan Feng, Zhijie Pan, Qinyao Li, Ai Wang, Yanfei Hu, Xueqian Xie

“…For each case, 6764 intratumor and peritumor radiomics features and 31 semantic features were collected. Multi-feature selections and decision tree models were performed on radiomics features and semantic features separately to select the most important features for Masaoka–Koga staging and WHO classification. …”
Get full text

Early Prediction of Battery Lifetime Using Centered Isotonic Regression with Quantile-Transformed Features by Muhammad Arslan Khan, Yixing Wang, Benben Jiang

“…Next, we adopt a centered isotonic regression (CIR) method in our work, a variant of isotonic regression (IR) that centers the feature values and then reduces overfitting to improve model performance. …”
Get full text

Parametric Aerodynamic Study of Galloping Piezoelectric Energy Harvester with Arcuate Protruding and Depressed Features by Xiaokang Yang, Bingke Xu, Zhendong Shang, Chunyang Liu, Haichao Cai, Xiangyi Hu

“…The aerodynamic characteristics and electrical performance are numerically analyzed, using a computational fluid dynamics model and a distributed parameter electromechanical coupling model, respectively. …”
Get full text

Target Detection Algorithm Based on Global Feature Fusion in Parallel Dual Path Backbone by QIU Yunfei, XIN Hao

“…Finally, the head adopts Ghost Conv combined with channel shuffling operation to maintain model performance and reduce parameter redundancy. …”
Get full text