Object Detection using YOLOv8 : A Systematic Review by Nugraha Asthra Megantara, Ema Utami

“…This study evaluates the performance of YOLOv8 based on precision, recall, F1-score, and mean average precision (mAP) metrics, and compares its advantages and limitations with previous YOLO versions and other object detection algorithms. Improvements in the YOLOv8 architecture, including attention mechanisms, improved feature extraction, and hyperparameter optimization, enable significant improvements in accuracy and computational efficiency, especially for small objects and low-light conditions. …”
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Target Detection Label Assignment Method Based on Global Information by ZHANG Pei-pei, LU Zhen-yu

“…With the development of deep learning framework, new object detection algorithms have also been proposed, such as first-stage and two-stage detection models, which have improved the detection speed and solved the problem of object detection at different scales, but they have not yet been well solved for overlapping, occlusion and other issues. …”
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Impact of Lexical Features on Answer Detection Model in Discussion Forums by Atif Khan, Muhammad Adnan Gul, Abdullah Alharbi, M. Irfan Uddin, Shaukat Ali, Bader Alouffi

“…Experimental results showed that the proposed answer detection model outperformed the baseline technique and other state-of-the-art machine learning algorithms in terms of classification accuracy on benchmark forum datasets.…”
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Experts fail to reliably detect AI-generated histological data by Jan Hartung, Stefanie Reuter, Vera Anna Kulow, Michael Fähling, Cord Spreckelsen, Ralf Mrowka

“…Here, we use stable diffusion, one of the most recent generative algorithms, to create such a set of artificial histological samples. …”
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Fake News Detection Using Machine Learning Ensemble Methods by Iftikhar Ahmad, Muhammad Yousaf, Suhail Yousaf, Muhammad Ovais Ahmad

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FDTooth: Intraoral Photographs and CBCT Images for Fenestration and Dehiscence Detection by Keyuan Liu, Marawan Elbatel, Guang Chu, Zhiyi Shan, Fung Hou Kumoi Mineaki Howard Sum, Kuo Feng Hung, Chengfei Zhang, Xiaomeng Li, Yanqi Yang

“…Currently, there is no public dataset that combines intraoral photographs and corresponding CBCT images; this limits the development of deep learning algorithms for the automated detection of FD and other potential diseases. …”
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Semi-supervised permutation invariant particle-level anomaly detection by Gabriel Matos, Elena Busch, Ki Ryeong Park, Julia Gonski

“…However, the typical machine learning (ML) algorithms employed for this task require fixed length and ordered inputs that break the natural permutation invariance in collision events. …”
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Custom YOLO Object Detection Model for COVID-19 Diagnosis by Noor Najah Ali, Aseel Hameed, Asanka G. Perera, Ali Al_Naji

“…Clinical staff can benefit from Computer Aided Diagnostics (CAD) systems that combine deep learning algorithms and image processing technologies as diagnostic tools for COVID-19. …”
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Detecting clinical medication errors with AI enabled wearable cameras by Justin Chan, Solomon Nsumba, Mitchell Wortsman, Achal Dave, Ludwig Schmidt, Shyamnath Gollakota, Kelly Michaelsen

“…We demonstrate that using deep learning algorithms, our system can detect and classify drug labels on syringes and vials in drug preparation events recorded in real-world operating rooms. …”
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A Review on Glaucoma Disease Detection Using Computerized Techniques by Faizan Daud, Rakhshanda Imtiaz, Hussain Ahmad Madni, Haroon Ahmed Khan, Tariq M. Khan, Mohammad A. U. Khan, Syed Saud Naqvi

“…These techniques measure OC and OC dimensions using machine learning based classification and segmentation algorithms. This article aims to provide a comprehensive overview of various existing techniques that use machine learning to detect and diagnose glaucoma based on fundus images. …”
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An annotated Dataset and Benchmark for Detecting Floating Debris in Inland Waters by Guangchao Qiao, Mingxiang Yang, Hao Wang

“…The dataset consists of 3000 images containing accurate annotation information to support vision-based water surface floater detection tasks. We conducted a number of baseline experiments to evaluate the performance of mainstream object detection algorithms on this dataset. …”
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Preset Conditional Generative Adversarial Network for Massive MIMO Detection by Yongzhi Yu, Shiqi Zhang, Jiadong Shang, Ping Wang

“…The detection performance of NR-PC-GAN is far superior to the other algorithms in low-SNR scenarios.…”
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Crack Detection in Civil Infrastructure: A Method-Scenario Review by Chang Haochen, Gu Weifan, Guo Baohua, Bassir David

“…This paper presents a systematic review of crack detection technologies organized under a novel “method-scenario” framework that categorizes techniques based on their underlying algorithms and the specific application contexts (e.g., pavements, bridges, tunnels, and specialized materials). …”
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Road Detection, Monitoring, and Maintenance Using Remotely Sensed Data by Nicholas Fiorentini, Massimo Losa

“…The ten papers published in this issue explore diverse methodologies, including novel deep learning algorithms for road inventory, novel methods for pavement crack detection, AI-enhanced ground-penetrating radar (GPR) imaging for subsurface assessment, high-resolution optical satellite imagery for unpaved road assessment, and aerial orthophotography for road mapping. …”
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Defect detection and localization in hydrogen pipelinesusing acoustic emission technique by Zi Wen Tham, Santhakumar Sampath, Lei Zhang

“…Furthermore, triangulation algorithms were employed to improve defect classification and localization accuracy. …”
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SEPDNet: simple and effective PCB surface defect detection method by Du Lang, Zhenzhen Lv

“…Abstract Replacing time-consuming and costly manual inspections on production lines with efficient and accurate defect detection algorithms for Printed Circuit Boards (PCBs) remains a significant challenge. …”
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Vision-Based Drone Detection in Complex Environments: A Survey by Ziyi Liu, Pei An, You Yang, Shaohua Qiu, Qiong Liu, Xinghua Xu

“…However, current reviews of vision-based drone detection are less focused on algorithmic summarization and analysis. …”
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Autonomous Driving Road Environment Recognition with Multiscale Object Detection by Jeny J.R.V., Divya Phulari, Varsha Kolanu, Mrunalini Anantha, Irfan S.K.M.

“…Using cutting-edge deep learning techniques, this research presents a novel way for autonomous road environment classification and item detection. It focuses on combining Yolov5 and multiscale small object detection models. …”
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A Survey of Data Stream-Based Intrusion Detection Systems by Rodrigo Sanches Miani, Gustavo Di Giovanni Bernardo, Guilherme Weigert Cassales, Hermes Senger, Elaine Ribeiro de Faria

“…Detecting malicious activities in network environments poses a challenge that attracts significant attention due to its complexity and importance. …”
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Machine Learning Model for Detecting Attack in Service Supply Chain by ASMAU OYINLADE OLANIYI, O. A Ayeni, M. G. Adewunmi

“…The study employs machine learning methods to increase the detection of service supply chain attacks, including Decision Trees, Random Forest, and XGBoost algorithms. …”
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