MRD: A Linear-Complexity Encoder for Real-Time Vehicle Detection by Kaijie Li, Xiaoci Huang

“…Vehicle detection algorithms constitute a fundamental pillar in intelligent driving systems and smart transportation infrastructure. …”
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A Novel Temporal Footprints-Based Framework for Fake News Detection by Ali Raza, Shafiq Ur Rehman Khan, Raja Sher Afgun Usmani, Ashok Kumar Das, Shehzad Ashraf Chaudhry

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A systematic review of ulcer detection methods in wireless capsule endoscopy by Ahmmad Musha, Rehnuma Hasnat, Abdullah Al Mamun, Md Sohag Hossain, Md Jakir Hossen, Tonmoy Ghosh

“…The contributions of this paper are two-fold: I) it reports and summarizes the current state-of-the-art ulcer detection algorithms; and II) it finds the most appropriate and preferable method in terms of color space, region of interest selection, feature extraction, and classifier. …”
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Deep Learning Based Early Intrusion Detection in IIoT using Honeypot by Abbasgholi Pashaei, Mohammad Esmaeil Akbari, Mina Zolfy Lighvan, Asghar Charmin

“…The accuracy of DL algorithms has been shown across a range of scientific fields. …”
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Design of a Heterogeneous-Based Network Intrusion Detection System and Compiler by Zhigui Lin, Xiaofeng Zhang, Qi Liu, Jun Cui

“…We construct an FPGA + CPU heterogeneous detection system featuring a five-tuple segmented matching architecture, which integrates hash bitmap and shift-or algorithms to achieve fast-pattern matching. …”
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RF-Based UAV Detection and Identification Enhanced by Machine Learning Approach by Yash Vasant Ahirrao, Rana Pratap Yadav, Sunil Kumar

“…This paper introduces the design and implementation of an RF-based system for detecting non-cooperating unmanned aerial vehicles (UAVs). …”
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A Critical Overview of Common Foodborne Toxicants and Methods for Their Reliable Detection by Betty Bowe Acquah, John‐Lewis Zinia Zaukuu

“…Therefore, analytical techniques are employed to detect and quantify these toxicants ensuring that they are within safe limits for consumption. …”
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Lung Cancer Detection Utilizing Mixed Sensor Based Electronic Nose by Umit Ozsandikcioglu, Ayten Atasoy, Yusuf Sevim

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From Misinformation to Insight: Machine Learning Strategies for Fake News Detection by Despoina Mouratidis, Andreas Kanavos, Katia Kermanidis

“…Beyond technical advancements, we explore the ethical implications of automated misinformation detection, addressing concerns related to censorship, algorithmic bias, and the trade-off between content moderation and freedom of expression. …”
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An exploration of machine learning approaches for early Autism Spectrum Disorder detection by Nawshin Haque, Tania Islam, Md Erfan

“…Similarly, the children dataset demonstrates outstanding results, achieving an mIoU of 100% for Support Vector Classifier and 99.96% for Logistic Regression. Furthermore, all algorithms achieved 100% accuracy on the children (age 4–11) dataset collected from real-world sources. …”
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Radiomics-based machine learning for automated detection of Pneumothorax in CT scans. by Hanieh Alimiri Dehbaghi, Karim Khoshgard, Hamid Sharini, Samira Jafari Khairabadi, Farhad Naleini

“…The used machine learning algorithms are Gradient Tree Boosting (GBM), eXtreme Gradient Boosting (XGBoost), and Light GBM. …”
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A novel feature selection technique: Detection and classification of Android malware by Sandeep Sharma, Prachi, Rita Chhikara, Kavita Khanna

“…Experimental results using machine learning algorithms demonstrate that the technique proposed in this research effectively integrates the advantages of individual feature selection techniques and exhibits the potential to identify a brief set of pivotal features for detecting Android malware. …”
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Research on a Burn Severity Detection Method Based on Hyperspectral Imaging by Sijia Wang, Minghui Gu, Mingle Zhang, Xin Tan

“…The accurate detection of burn wounds is a key research direction in the field of burn medicine, as diagnostic results directly influence the risk of wound infection and the formation of hypertrophic scars. …”
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Mitigating Catastrophic Forgetting in Pest Detection Through Adaptive Response Distillation by Hongjun Zhang, Zhendong Yin, Dasen Li, Yanlong Zhao

“…Pest detection in agriculture faces the challenge of adapting to new pest species while preserving the ability to recognize previously learned ones. …”
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A Lightweight YOLO-Based Architecture for Apple Detection on Embedded Systems by Juan Carlos Olguín-Rojas, Juan Irving Vasquez, Gilberto de Jesús López-Canteñs, Juan Carlos Herrera-Lozada, Canek Mota-Delfin

“…In Mexico, the manual detection of damaged apples has led to inconsistencies in product quality, a problem that can be addressed by integrating vision systems with machine learning algorithms. …”
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Detecting performance difficulty of learners in colonoscopy: Evidence from eye-tracking by Xin Liu, Bin Zheng, Xiaoqin Duan, Wenjing He, Yuandong Li, Jinyu Zhao, Chen Zhao, Lin Wang

“…We applied deep learning algorithms to detect the eye-tracking metrics on the moments of navigation lost (MNL), a signature sign for performance difficulty during colonoscopy. …”
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Investigating the Use of Electrooculography Sensors to Detect Stress During Working Activities by Alessandra Papetti, Marianna Ciccarelli, Andrea Manni, Andrea Caroppo, Gabriele Rescio

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Comprehensive Review of Intrusion Detection Techniques: ML and DL in Different Networks by Imane Rakine, Aziz Oukaira, Kamal El Guemmat, Issam Atouf, Sara Ouahabi, Mohamed Talea, Tarik Bouragba

“…The strengths and limitations of ML and DL algorithms, which are frequently used for intrusion detection, are highlighted. …”
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Detection of cotton crops diseases using customized deep learning model by Hafiz Muhammad Faisal, Muhammad Aqib, Saif Ur Rehman, Khalid Mahmood, Silvia Aparicio Obregon, Rubén Calderón Iglesias, Imran Ashraf

“…Thanks to deep learning algorithms, researchers have developed innovative disease detection approaches that can help safeguard the cotton crop and promote economic growth. …”
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SD-YOLOv8: Automated Motion Detection System for Aerobics Students by Lian Tang, Ya Li, Qing Du, Jincheng Liang

“…Existing object detection algorithms are often constrained by the high computational costs associated with large network structures in practical applications. …”
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