MeStanG—Resource for High-Throughput Sequencing Standard Data Sets Generation for Bioinformatic Methods Evaluation and Validation by Daniel Ramos Lopez, Francisco J. Flores, Andres S. Espindola

“…Metagenomics analysis has enabled the measurement of the microbiome diversity in environmental samples without prior targeted enrichment. Functional and phylogenetic studies based on microbial diversity retrieved using HTS platforms have advanced from detecting known organisms and discovering unknown species to applications in disease diagnostics. …”
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Improving dependability with low power fault detection model for skinny-hash. by Sonal Arvind Barge, Gerardine Immaculate Mary

“…Two fault detection approaches are proposed to detect faults in cryptographic algorithms running on IoT devices. …”
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Study on lightweight strategies for L-YOLO algorithm in road object detection by Ji Hong, Kuntao Ye, Shubin Qiu

“…The demand for real-time, efficient object detection systems is growing. However, traditional algorithms often suffer from large parameter sizes and high computational costs, limiting their applicability in resource-constrained environments. …”
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Water quality anomaly detection research based on GRU-PINN model by Zhao Xinyu

“…Maintaining high-quality water resources is essential for sustainable urban water resource management and public health. …”
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High-Sensitivity, Low Detection Limit, and Fast Ammonia Detection of Ag-NiFe₂O₄ Nanocomposite and DFT Study by Xianfeng Hao, Yuehang Sun, Zongwei Liu, Gongao Jiao, Dongzhi Zhang

“…This study facilitates the rapid detection of food spoilage and promotes the development of portable food safety detection devices.…”
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SR-DETR: Target Detection in Maritime Rescue from UAV Imagery by Yuling Liu, Yan Wei

“…These outcomes highlight the practicality and reliability of our method in detecting individuals overboard, contributing to more precise and resource-efficient solutions for real-time maritime rescue efforts.…”
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SWMD-YOLO: A Lightweight Model for Tomato Detection in Greenhouse Environments by Quan Wang, Ye Hua, Qiongdan Lou, Xi Kan

“…This study proposes SWMD-YOLO, a lightweight multi-scale detection network optimized for greenhouse scenarios. …”
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Comparative Analysis of Deep Learning Models for Intrusion Detection in IoT Networks by Abdullah Waqas, Sultan Daud Khan, Zaib Ullah, Mohib Ullah, Habib Ullah

“…However, the constrained processing capacities and resource limitations of IoT networks make them especially susceptible to cyber threats. …”
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RipFinder: real-time rip current detection on mobile devices by Fahim Khan, Akila de Silva, Ashleigh Palinkas, Gregory Dusek, James Davis, Alex Pang

“…To address this, we propose a client-server ML model-based computer vision system designed specifically to improve rip current detection accuracy. This novel approach enables the app to function with or without internet connectivity, proving particularly beneficial in regions without lifeguards or internet access. …”
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Pavement Disease Visual Detection by Structure Perception and Feature Attention Network by Bin Lv, Shuo Zhang, Haixia Gong, Hongbo Zhang, Bin Dong, Jianzhu Wang, Cong Du, Jianqing Wu

“…Balancing detection performance and computational efficiency is critical for sustainable pavement disease detection in energy-constrained scenarios. …”
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Ultra-sensitive terahertz photonic crystal fiber sensor for detection of tuberculosis by Md. Safiul Islam, A.H.M. Iftekharul Ferdous, Abdullah Al Mamun, Md. Shamim Anower, Md. Jakir Hossen, Syed Udoy Ahmed

“…This sensing unit under consideration can function within the terahertz frequency range. Consequently, it serves as a valuable resource for healthcare providers, enhancing their diagnostic capabilities for prompt treatment and improved patient outcomes. …”
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LiteTom-RTDETR: A Lightweight Real-Time Tomato Detection System for Plant Factories by Wenshuai Liu, Qingzheng Liu, Wenyong Quan, Junli Wang, Xiaomin Yao, Qiang Liu, Yuxiang Tian

“…The accuracy and speed of tomato detection were increased to facilitate fully automated harvesting by improving the Real-Time Detection Transformer (RTDETR) to develop a new lightweight tomato detection model called LiteTom-RTDETR. …”
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Downstream Semantic Segmentation Model for Low-Level Surface Crack Detection by Thitirat Siriborvornratanakul

“…The most successful downstream model we found is trained by the focal loss function without using the pretrained weights that are accompanied by the base model. …”
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Discrimination of mercury, cadmium and lead polluted rice leaves based on near infrared spectroscopy technology by ZHANG Long, PAN Jiarong, ZHU Cheng

“…There are hundreds of sources of heavy metal pollution, including the industries of coal, natural gas, paper, and mining. …”
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A Route to the Colorimetric Detection of Alpha-Fetoprotein Based on a Smartphone by Junjie Liu, Qingfubo Geng, Zhaoxin Geng

“…Alpha-fetoprotein (AFP) is a key marker for early cancer detection and assessment. However, the current detection methods struggle to balance accuracy with the need for decentralized medical treatment. …”
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Interpretable Chinese Fake News Detection With Chain-of-Thought and In-Context Learning by Bingyi Liu, Anqi Wang, Chengqian Xia

“…The spread of fake news through on-line platforms poses a significant threat to public trust and social stability, especially in resource-constrained Chinese domains. Existing Fake News Detection (FND) models often lack transparency, functioning as “black boxes” that limit their practical utility. …”
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Cheating Detection in Online Exams Using Deep Learning and Machine Learning by Bahaddin Erdem, Murat Karabatak

“…In the regression analysis conducted within the scope of Scenario-1, the model we proposed to detect “cheating” behavior, which is one of the unethical learner behaviors, was found to be a 5-layer DNN model with a test performance success of 80.9%. …”
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TEDVIL: Leveraging Transformer-Based Embeddings for Vulnerability Detection in Lifted Code by Gary A. McCully, John D. Hastings, Shengjie Xu

“…Notably, these results are achieved when the embedding model is trained with a dataset of just 48,000 functions, demonstrating effectiveness in resource-constrained settings. …”
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Gas Detection and Classification Using Neural Network Based Gas Sensors by Munaf Ismail, Sri Arttini Dwi Prasetyowati

“…The MQ-3 gas sensor successfully reads liquid vapor in alcohol with levels of 30%, 50%, 70%, and other water-based liquids. …”
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Fuzzy deep learning architecture for cucumber plant disease detection and classification by Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu

“…The proposed approach is efficient and feasible, offering a more stable and accurate disease detection system while utilizing fewer resources. This work demonstrates the potential of AI-driven solutions in agriculture, particularly in improving disease detection and crop yield through advanced machine learning techniques.…”
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