Plant disease detection with generative adversarial networks by Garam Han, Derek Kwaku Pobi Asiedu, Kwabena Ebo Bennin

“…Generative Adversarial Networks (GANs) have emerged as a promising approach for enhancing image detection and facilitating image classification. Deep learning models, which exhibit high classification accuracy, have proven advantageous over conventional approaches for Plant disease detection (PDD). …”
Get full text

Customer Attrition Detection Using the LGBM Model by Huang Jie

“…To select the most suitable model for accurately detecting customer churn, this study performs preprocessing, including data cleaning, feature engineering, and feature selection. …”
Get full text

Moving Objects Detection Based on Frequency Domain by jalal hameed awad, Balsam Dhyia Majeed

Get full text

Modern Psychoactive Substances and Their Detection in Biomedical Samples by A. M. Grigoryev, V. N. Fateenkov

“…The purpose of the work is to review psychoactive compounds and methods of their detection performed for diagnostic purposes. The paper presents brief characteristics of the most common NPS, as well as features of their metabolism in the human. …”
Get full text

PHENOTYPIC FEATURES AND CHEMILUMINESCENT ACTIVITY OF NEUTROPHILIC GRANULOCYTES IN THE PATIENTS WITH RENAL CANCER by A. A. Savchenko, A. G. Borisov, A. A. Modestov, I. V. Kudryavtsev, A. V. Moshev, I. I. Gvozdev, O. G. Tonacheva

Get full text

Features of defecation dysfunction among patients with Hirschsprung disease in early childhood by Shiwen Pan, Wei Li, Chengpeng Shi, Weibing Tang, Changgui Lu

“…Abstract Background Defecation dysfunction among patients with Hirschsprung disease (HD) in early childhood may persist into adulthood and lead to social problems. The features of defecation dysfunction in HD patients with different aganglionic segment lengths during early childhood have not been established. …”
Get full text

Molecular features of renal cell carcinoma: early diagnostics and perspectives for therapy by O. V. Kovaleva, O. R. Nazarova, V. B. Matveev, A. N. Gratchev

Get full text

Arabic web pages clustering and annotation using semantic class features by Hanan M. Alghamdi, Ali Selamat, Nor Shahriza Abdul Karim

“…To effectively manage the great amount of data on Arabic web pages and to enable the classification of relevant information are very important research problems. Studies on sentiment text mining have been very limited in the Arabic language because they need to involve deep semantic processing. …”
Get full text

Causes of intraventricular hemorrhages in extremely premature newborns and features of their early outcomes by V. V. Kocherova, N. G. Popova, V. A. Shcherbak

Get full text

PFW-YOLO Lightweight Helmet Detection Algorithm by Yue Hong, Hao Wang, Shuo Guo

“…Second, in order to further reduce the size of the model while ensuring the detection accuracy, Feature Interaction Shared Detection Head (FISH) is introduced. …”
Get full text

Automatic tag detection in multimedia survey condition by M. Russo, L. Martelli, R. Ravanelli, A. Pini

“…This paper focuses on such technical problems, presenting part of the qualitative and quantitative results obtained at this stage of our research and the approach used to resolve some detection limitations.…”
Get full text

Malware detection approach based on improved SOINN by Bin ZHANG, Lixun LI, Shuqin DONG

“…To deal with the problems of dynamic update of detection model and high computation costs in malware detection model based on batch learning,a novel malware detection approach is proposed by combing SOINN and supervised classifiers,to reduce computation costs and enable the detection model to update dynamically with the assistance of SOINN′s incremental learning characteristic.Firstly,the improved SOINN was given.According to the whole alignment algorithm,search the adjusted weights of neurons under all input sequences in the learning cycle and then calculate the average value of all adjusted weights as the final result,to avoid SOINN′s stability under different input sequences and representativeness of original data,therefore improve malware detection accuracy.Then a data preprocessing algorithm was proposed based on nonnegative matrix factor and Z-score normalization to transfer the malware behavior feature vector from high dimension and high order to low dimension and low order,to speed up and avoid overfitting and further improve detection accuracy.The results of experiments show that proposed approach supports dynamic updating of detection model and has a significantly higher accuracy of detecting unknown new samples and lower computation costs than tradition methods.…”
Get full text

An Adaptive Threshold-Based Pixel Point Tracking Algorithm Using Reference Features Leveraging the Multi-State Constrained Kalman Filter Feature Point Triangulation Technique for D... by Zohaib Wahab Memon, Yu Chen, Hai Zhang

“…Tracking arbitrary featureless pixel points alongside traditional features ensures a real-time depth map of the surroundings, which can be applied to various applications, including obstacle detection, collision avoidance, and path planning.…”
Get full text

Theoretical and Methodological Features of the Analysis of the Basic Concepts of the Modern Theory of National Security by A. B. Feonichev, K. Yu. Meleshin

Get full text

Histopathological Study of Urinary Bladder Cancer in a Group of Iraqi Patients from 2019 to 2024 by Zhraa D. Salman, Ban J. Mohamad

Get full text

Multiscale Feature Filtering Network for Image Recognition System in Unmanned Aerial Vehicle by Xianghua Ma, Zhenkun Yang, Shining Chen

“…To solve this problem, a multiscale feature filtering network (MFFNet) is proposed in this paper for image recognition system in the UAV. …”
Get full text

A New Approach for Clustered MCs Classification with Sparse Features Learning and TWSVM by Xin-Sheng Zhang

“…We formulate this classification problem as sparse feature learning based classification on behalf of the test samples with a set of training samples, which are also known as a “vocabulary” of visual parts. …”
Get full text

Analysis of super-long and sparse feature in pseudo-random sequence based on similarity by Chun-jie CAO, Jing-zhang SUN, Zhi-qiang ZHANG, Long-juan WANG, Meng-xing HUANG

“…Similarity analysis of pseudo-random sequence in wireless communication networks is a research hotspot problem in the domain of information warfare.Based on the difficulties in super-long sequence,extremely sparse feature,and futilities in engineering application for real-time processing exist in similarity analysis of sequence in wireless net-work,a method of similarity analysis of sequence in a certain margin of misacceptance probability was proposed.Firstly,the similarity probability distribution of real-random sequence was theoretically analyzed.Secondly,according to the standard of NIST SP 800-22,the randomness of pseudo-bitstream was analyzed and the validity of pseudo-bitstream was judged.Finally,similarity was analyzed and verified by combining super-long pseudo-random sequence in real wireless communication networks.The results indicate that the lower bound of similarity value is 0.62 when misacceptance prob-ability uncertainty at about 1%.Above conclusion is considerable importance from the significance and theoretical values in network security domains,such as protocol analysis,traffic analysis,intrusion detection and others.…”
Get full text

Small target detection algorithm based on SAHI-Improved-YOLOv8 for UAV imagery: A case study of tree pit detection by Xiuhao Liang, Jun Xiang, Sheng Qin, Yundan Xiao, Lifen Chen, Dongxia Zou, Honglun Ma, Dong Huang, Yongxin Huang, Wei Wei

“…The application of deep learning in tree pit detection of unmanned aerial vehicle (UAV) images has problems such as dense distribution, high density, small size, false detections, missed detections, and high localization error. …”
Get full text

Optimization and Validation of Wafer Surface Defect Detection Algorithm Based on RT-DETR by Ao Xu, Yanwei Li, Hongbo Xie, Rui Yang, Jianjie Li, Jiaying Wang

“…Firstly, a dynamic snake convolutional layer is introduced to detect elongated scratches where conventional convolutional kernels fail to extract features effectively. …”
Get full text