Blockchain-Enabled Deep Recurrent Neural Network Model for Clickbait Detection by Abdul Razaque, Bandar Alotaibi, Munif Alotaibi, Fathi Amsaad, Ansagan Manasov, Salim Hariri, Banu B. Yergaliyeva, Aziz Alotaibi

“…To achieve the clickbait analysis and source rating, the detection of blocklisted/allowlisted source and source rating check algorithms are introduced. …”
Get full text

Integrating Information Gain and Chi-Square for Enhanced Malware Detection Performance by Fauzi Adi Rafrastara, Wildanil Ghozi, Ramadhan Rakhmat Sani, Lekso Budi Handoko, Abdussalam Abdussalam, Elkaf Rahmawan Pramudya, Faizal M. Abdollah

“…Recent studies have shown that this challenge can be addressed by employing machine learning algorithms for detection. Some studies have also implemented various feature selection methods to optimize detection efficiency. …”
Get full text

Infrared dim tiny-sized target detection based on feature fusion by Peng Zhang, Yaman Jing, Guodong Liu, Ziyang Chen, Xiaoyan Wu, Osami Sasaki, Jixiong Pu

“…These two main modules are employed as the core to form a feature fusion network to realize the detection of infrared dim tiny-sized targets. The comparison of the proposed network with other algorithms are performed on open-source dataset and experimentally generated infrared images. …”
Get full text

Lightweight and robust ship detection method driven by self-attention mechanism by Feng MA, Zihui SHI, Jie SUN, Chen CHEN, Xianbin MAO, Xinping YAN

“…During testing, the proposed method demonstrates superior overall ship detection performance compared to other algorithms, with a mAP of 92.9%, a precision rate of 92.1%, and a parameter size of 35 366 310. …”
Get full text

Detection of Mycotoxin Contamination in Foods Using Artificial Intelligence: A Review by Ashish Aggarwal, Akanksha Mishra, Nazia Tabassum, Young-Mog Kim, Fazlurrahman Khan

“…Deep learning models, machine learning algorithms, and neural networks were implemented to analyze elaborate datasets from different analytical platforms. …”
Get full text

Deep Learning in Defect Detection of Wind Turbine Blades: A Review by Katleho Masita, Ali N. Hasan, Thokozani Shongwe, Hasan Abu Hilal

“…The paper concludes by emphasizing the transformative potential of deep learning in achieving automated, accurate, and efficient defect detection in wind turbine blades. Addressing current limitations through interdisciplinary research and innovative algorithms will pave the way for sustainable and cost-effective wind energy systems, ultimately contributing to the global transition toward renewable energy.…”
Get full text

A machine learning model for early detection of sexually transmitted infections by Juma Shija, Judith Leo, Elizabeth Mkoba

“…The purpose of this paper is to present a machine-learning model for early detection of sexually transmitted infections that was developed. …”
Get full text

Early detection of retinal and choroidal microvascular impairments in diabetic patients with myopia by Yufei Wu, Yufei Wu, Jiahui Jiang, Xiaoyu Deng, Xixi Zhang, Jinger Lu, Zian Xu, Yitian Zhao, Zai-Long Chi, Zai-Long Chi, Qinkang Lu, Qinkang Lu

“…The integration of SS-OCTA with artificial intelligence-enhanced segmentation and vascular analysis provides a refined method for early detection of retinal and choroidal microvascular impairments in diabetic populations.…”
Get full text

A public benchmark for human performance in the detection of focal cortical dysplasia by Lennart Walger, Matthias H. Schmitz, Tobias Bauer, David Kügler, Fabiane Schuch, Christophe Arendt, Tobias Baumgartner, Johannes Birkenheier, Valeri Borger, Christoph Endler, Franziska Grau, Christian Immanuel, Markus Kölle, Patrick Kupczyk, Asadeh Lakghomi, Sarah Mackert, Elisabeth Neuhaus, Julia Nordsiek, Anna‐Maria Odenthal, Karmele Olaciregui Dague, Laura Ostermann, Jan Pukropski, Attila Racz, Klaus von derRopp, Frederic Carsten Schmeel, Felix Schrader, Aileen Sitter, Alexander Unruh‐Pinheiro, Marilia Voigt, Martin Vychopen, Philip vonWedel, Randi vonWrede, Ulrike Attenberger, Hartmut Vatter, Alexandra Philipsen, Albert Becker, Martin Reuter, Elke Hattingen, Alexander Radbruch, Rainer Surges, Theodor Rüber

“…A myriad of algorithms for automated FCD detection have been developed, but their true clinical value remains unclear since there is no benchmark dataset for evaluation and comparison to human performance. …”
Get full text

Deepfake Audio Detection for Urdu Language Using Deep Neural Networks by Omair Ahmad, Muhammad Sohail Khan, Salman Jan, Inayat Khan

“…Therefore, developing effective algorithms to distinguish fake audio from real audio is critical to preventing such frauds. …”
Get full text

Digital visual media forensics by Chun-hui FENG, Zheng-quan XU, Xing-hui ZHENG, Li JIANG

“…The origin and concept of digital visual media forensics is introduced, representative double compression de-tection and forgery detection algorithms are introduced in detail afterwards. …”
Get full text

Assessing change point detection methods to enable robust detection of early stage Artisanal and Small-Scale mining (ASM) in the tropics using Sentinel-1 time series data by Mensah Isaac Obour, Barrett Brian, Cahalane Conor

“…This study utilised a time series smoothing technique to improve Sentinel-1 (S-1) SAR time series data, reducing SAR noise and atmospheric effects from heavy rainfall for early ASM activity detection. We tested three change point detection (CPD) methods, including cumulative sum (CuSuM), pruned exact linear time (PELT), and binary segmentation (BinSeg) in the Western and Ashanti wet regions in southern Ghana using the smoothed S-1 data for early ASM detection. …”
Get full text

Multi task detection method for operating status of belt conveyor based on DR-YOLOM by Yongan LI, Tengjie CHEN, Hongwei WANG, Zhihao ZHANG

“…The results show that compared to mainstream single detection algorithms, DR-YOLOM multi task detection algorithm has better comprehensive detection ability, and this algorithm can ensure high target recognition accuracy, segmentation accuracy, and appropriate inference speed with a small number of parameters. …”
Get full text

Detecting Emerging DGA Malware in Federated Environments via Variational Autoencoder-Based Clustering and Resource-Aware Client Selection by Ma Viet Duc, Pham Minh Dang, Tran Thu Phuong, Truong Duc Truong, Vu Hai, Nguyen Huu Thanh

“…Domain Generation Algorithms (DGAs) remain a persistent technique used by modern malware to establish stealthy command-and-control (C&C) channels, thereby evading traditional blacklist-based defenses. …”
Get full text

Railway Tracks Extraction from High Resolution Unmanned Aerial Vehicle Images Using Improved NL-LinkNet Network by Jing Wang, Xiwei Fan, Yunlong Zhang, Xuefei Zhang, Zhijie Zhang, Wenyu Nie, Yuanmeng Qi, Nan Zhang

“…The accurate detection of railway tracks from unmanned aerial vehicle (UAV) images is essential for intelligent railway inspection and the development of electronic railway maps. …”
Get full text

A Lightweight and Efficient Plant Disease Detection Method Integrating Knowledge Distillation and Dual-Scale Weighted Convolutions by Xiong Yang, Hao Wang, Qi Zhou, Lei Lu, Lijuan Zhang, Changming Sun, Guilu Wu

Get full text

Early Detection of Alzheimer’s Disease Using Generative Models: A Review of GANs and Diffusion Models in Medical Imaging by Md Minul Alam, Shahram Latifi

Get full text

Improving Vertebral Fracture Detection in C-Spine CT Images Using Bayesian Probability-Based Ensemble Learning by Abhishek Kumar Pandey, Kedarnath Senapati, Ioannis K. Argyros, G. P. Pateel

Get full text

PCR-detection rates of T. pallidum ssp. pallidum in swab samples from the Czech Republic (2004–2022): Combined RPR, IgM, and PCR tests efficiently detect active syphilis by Eliška Vrbová, Petra Pospíšilová, Eliška Dastychová, Martina Kojanová, Miluše Kreidlová, Daniela Vaňousová, Filip Rob, Přemysl Procházka, Alena Krchňáková, Vladimír Vašků, Radim Strnadel, Olga Faustmannová, Monika Dvořáková Heroldová, Ivana Kuklová, Hana Zákoucká, David Šmajs

“…Our findings show that the reverse algorithm for detecting syphilis could be substantially improved by adding IgM and PCR testing.…”
Get full text

YOLOv3-A: a traffic sign detection network based on attention mechanism by Fan GUO, Yongxiang ZHANG, Jin TANG, Weiqing LI

“…To solve the problem that the existing YOLOv3 algorithm had more false detections and missed detections for traffic sign detection task with small target problems and complex background, based on the YOLOv3, a channel attention method for target detection and a spatial attention method based on semantic segmentation guidance were proposed to form the YOLOv3-A (attention) algorithm.The detection features in the channel and spatial dimensions were recalibrated, allowing the network to focus and enhance the effective features, and suppress interference features, which greatly improved the detection performance.Experiments on the TT100K traffic sign data set show that the algorithm improves the detection performance of small targets, and the accuracy and recall rate of the YOLOv3 are improved by 1.9% and 2.8% respectively.…”
Get full text