Small Target Detection Algorithm for UAV Aerial Images Based on Improved YOLOv7-tiny by ZHANG Guanghua, LI Congfa, LI Gangying, LU Weidang

“…Among these, the pedestrian, people, and motor categories show especially strong detection performance. 4) The detection performance of the improved algorithm is verified in real-world scenarios through comparative analysis. …”
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A Study on Instantaneous Time-Frequency Methods for Damage Detection of Nonlinear Moment-Resisting Frames by Ehsan Darvishan, Gholamreza Ghodrati Amiri, Pedram Ghaderi

“…A probabilistic approach is implemented to investigate capability of the procedure for different ground motion records using incremental dynamic analysis. Results show that frequency is not an appropriate feature to detect damage in nonlinear structures.…”
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A novel fusion architecture for detecting Parkinson’s Disease using semi-supervised speech embeddings by Tariq Adnan, Abdelrahman Abdelkader, Zipei Liu, Ekram Hossain, Sooyong Park, Md Saiful Islam, Ehsan Hoque

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Future of Alzheimer's detection: Advancing diagnostic accuracy through the integration of qEEG and artificial intelligence by Sahar Rezaei, Farzan Asadirad, Alireza Motamedi, Mohammadsadegh Kamran, Farzaneh Parsa, Haniyeh Samimi, Parna Ghannadikhosh, Mahdi Zahmatyar, Seyed Ali Hosseinzadeh, Hossein Arabi

“…Through systematic analysis of 11 key studies across multiple international databases, we evaluated various AI architectures, including machine learning algorithms and deep learning networks, applied to qEEG data for AD detection. …”
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The Neural Frontier of Future Medical Imaging: A Review of Deep Learning for Brain Tumor Detection by Tarek Berghout

“…By analyzing over 100 research papers over past half-decade (2019–2024), this review fills that gap, exploring the latest methods and paradigms, summarizing key concepts, challenges, datasets, and offering insights into future directions for brain tumor detection using deep learning. This review also incorporates an analysis of previous reviews and targets three main aspects: feature extraction, segmentation, and classification. …”
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Enhancing Brain Tumor Detection: A Comparative Study of CNN Architectures Using MRI Data by Zhu Zhimeng

“…VGG19-BMT incorporates targeted optimizations, including adjustments to convolutional layers and improved feature extraction modules. A systematic comparative analysis of VGG19-BMT and traditional CNN models was conducted using the Kaggle dataset “Brain MRI Images for Brain Tumor Detection.” …”
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Resilience of Machine Learning Models in Anxiety Detection: Assessing the Impact of Gaussian Noise on Wearable Sensors by Abdulrahman Alkurdi, Jean Clore, Richard Sowers, Elizabeth T. Hsiao-Wecksler, Manuel E. Hernandez

“…The effectiveness of feature-based and end-to-end machine learning models for anxiety detection was evaluated under varying conditions of Gaussian noise. …”
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High-Throughput 3D Rice Chalkiness Detection Based on Micro-CT and VSE-UNet by Zhiqi Cai, Yangjun Deng, Xinghui Zhu, Bo Li, Chenglin Xu, Donghui Li

“…This framework overcomes the limitations of single-grain analysis, enabling simultaneous multi-grain detection. …”
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Sensor Array System Based on Electronic Nose to Detect Borax in Meatballs with Artificial Neural Network by Anak Agung Surya Pradhana, Suryani Dyah Astuti, null Fauziah, Perwira Annissa Dyah Permatasari, Riskia Agustina, Ahmad Khalil Yaqubi, Harsasi Setyawati, null Winarno, Cendra Devayana Putra

“…Artificial neural networks (ANNs) and principal component analysis (PCA), which are beneficial for feature extraction and classification, are used to handle the collected data based on machine learning approaches. …”
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Detection of Oil Mineral Pollution in Tigris River from Aldora Refined using Absorbance Spectroscopy by Thamer Mahmood Mohammed, Ahmed K. Ahmed

“…It is fast, accurate data analysis, and a lower cost compared with the other chemical analysis and conventional methods. …”
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Detection of intracranial hypertension in children using optical coherence tomography: a systematic review protocol by Sohaib R Rufai, Noor ul Owase Jeelani, Rebecca J McLean

“…Here, we propose a systematic review protocol to examine the role of OCT in the detection of ICH in children.Methods and analysis Electronic searches in the Cochrane Central Register of Controlled Trials, Medline, Embase, Web of Science and PubMed will identify studies featuring OCT in detecting ICH in children. …”
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Highly sensitive cancer detection using an open D-channel PCF-based SPR biosensor by Mahla Ashrafian, Saeed Olyaee, Mahmood Seifouri

“…Abstract Surface plasmon resonance (SPR) is a technique utilized for the label-free detection of cancer cells. In this analysis, we introduce a photonic crystal fiber (PCF) designed with an open D-channel, featuring a layer of gold (Au) and titanium dioxide (TiO2) as the plasmonic material. …”
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Detection of disease on nasal breath sound by new lightweight architecture: Using COVID-19 as an example by Jiayuan She, Lin Shi, Peiqi Li, Ziling Dong, Renxing Li, Shengkai Li, Liping Gu, Zhao Tong, Zhuochang Yang, Yajie Ji, Liang Feng, Jiangang Chen

“…Additional feature selection was performed using random forest (RF) and principal component analysis (PCA) for dimensionality reduction. …”
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Automated Pipeline for Robust Cat Activity Detection Based on Deep Learning and Wearable Sensor Data by Md Ariful Islam Mozumder, Tagne Poupi Theodore Armand, Rashadul Islam Sumon, Shah Muhammad Imtiyaj Uddin, Hee-Cheol Kim

“…Our study culminates in the development of an automated system for robust pet (cat) activity analysis using artificial intelligence techniques, featuring a 1D-CNN-based approach. …”
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Employing convolutional neural networks and explainable artificial intelligence for the detection of seizures from electroencephalogram signal by Tamilarasi Kathirvel Murugan, Anush Kameswaran

“…To identify the EEG data, the proposed system combines deep learning models with feature extraction technique. Model visualization and XAI approaches like feature importance analysis from SHAP values offer clear insights into the model's decision-making process. …”
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Practical Malware Analysis by D. A. Elizarov, A. V. Katkov

“…The main task is to analyze malware to assess threats and timely detection and take action.Method. For analysis, you should use an isolated environment with a customized environment and software.Result. …”
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AI may help to predict thyroid nodule malignancy based on radiomics features from [18F]FDG PET/CT by Krystian Ślusarz, Mikolaj Buchwald, Adrian Szczeszek, Szymon Kupinski, Anna Gramek-Jedwabna, Wojciech Andrzejewski, Juliusz Pukacki, Robert Pękal, Marek Ruchała, Rafał Czepczyński, Cezary Mazurek

“…Conclusions With an AI-based algorithm using radiomics features it is possible to detect the malignancy of thyroid nodule. …”
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A novel machine learning model for perimeter intrusion detection using intrusion image dataset. by Shahneela Pitafi, Toni Anwar, I Dewa Made Widia, Zubair Sharif, Boonsit Yimwadsana

“…Perimeter Intrusion Detection Systems (PIDS) are crucial for protecting any physical locations by detecting and responding to intrusions around its perimeter. …”
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Cervical Cancer Detection Using Deep Neural Network and Hybrid Waterwheel Plant Optimization Algorithm by Sarah A. Alzakari, Amel Ali Alhussan, S.K. Towfek, Marwa Metwally, Dina Ahmed Salem

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Salient object detection dataset with adversarial attacks for genetic programming and neural networksMendeley Data by Matthieu Olague, Gustavo Olague, Roberto Pineda, Gerardo Ibarra-Vazquez

“…However, security concerns about its robustness to malicious and imperceptible perturbations have drawn attention since humans or machines can change the predictions of programs entirely. Salient object detection is a research area where deep convolutional neural networks have proven effective but whose trustworthiness represents a significant issue requiring analysis and solutions to hackers' attacks. …”
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