LAVID: A Lightweight and Autonomous Smart Camera System for Urban Violence Detection and Geolocation by Mohammed Azzakhnini, Houda Saidi, Ahmed Azough, Hamid Tairi, Hassan Qjidaa

“…Furthermore, our approach, implemented using optimized deep learning models and evaluated on several public datasets, has shown good results in term of accuracy compared to state of the art methods while optimizing reducing power and computational requirements.…”
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GDSN-CD: Graph-Guided Diffusion Synergistic Network for Remote Sensing Change Detection by Yunfei Zhu, Jintao Song, Jinjiang Li

“…Experimental results show that GDSN-CD significantly outperforms mainstream methods on three public datasets, especially in fine-grained change detection and anti-interference capability, demonstrating strong potential for practical applications.…”
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BiAF: research on dynamic goat herd detection and tracking based on machine vision by Yun Hou, Mingjuan Han, Wei Fan, Xinyu Jia, Zhuo Gong, Ding Han

“…In this paper, we propose a machine vision-based grazing goat herd detection algorithm that enhances the streamlined ELAN module in YOLOv7-tiny, incorporates an optimized CBAM attention mechanism, refines the SPPCSPC module to reduce the parameter count, and improves the anchor boxes in YOLOv7-tiny to enhance target detection accuracy. …”
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Detecting sand gradation based on the two-dimensional sand particle features in sand images by Chuanyun Xu, Heng Wang, Yang Zhang, Song Sun, Gang Li

“…Existing machine learning-based automated detection methods have limited accuracy, and deep learning is hindered by difficulties in image data annotation and the lack of high-quality datasets, which affect its application effectiveness.To address this, this paper proposes a detection method based on the two-dimensional sand particle features in sand images. …”
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AnomalGRN: deciphering single-cell gene regulation network with graph anomaly detection by Zhecheng Zhou, Jinhang Wei, Mingzhe Liu, Linlin Zhuo, Xiangzheng Fu, Quan Zou

“…Considering the imbalance between positive and negative links in GRNs, we further adapt this issue into a graph anomaly detection (GAD) task, marking the first application of anomaly detection to GRN analysis. …”
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Machine Learning for Accurate Office Room Occupancy Detection Using Multi-Sensor Data by Yusuf Ibrahim, Umar Yusuf Bagaye, Abubakar Ibrahim Muhammad

“…The results obtained highlight the efficacy and suitability of varying candidate and ensemble methods, demonstrating the potential of ML techniques in enhancing detection accuracy. …”
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Multi-Branch Network with Multi-Feature Enhancement for Improving the Generalization of Facial Forgery Detection by Siyu Meng, Quange Tan, Qianli Zhou, Rong Wang

“…With the advent of diffusion models, the realism of forged facial images has increased, making detection increasingly challenging. However, the existing detection methods primarily focus on identifying facial forgeries generated by generative adversarial networks; they may struggle to generalize when faced with novel forgery techniques like diffusion models. …”
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Artificial Intelligence for DC Arc Fault Detection in Photovoltaic Systems: A Comprehensive Review by Kamal Chandra Paul, Disnebio Waldmann, Chen Chen, Yao Wang, Tiefu Zhao

“…Traditional detection methods often fall short in terms of accuracy, prompting growing interest in artificial intelligence (AI)-based solutions. …”
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Long-Range LiDAR Vehicle Detection Through Clustering and Classification for Autonomous Racing by Na-Young Lim, Tae-Hyoung Park

“…These results underscore the novelty and effectiveness of the proposed method as an optimized solution for long-range vehicle detection in real-time autonomous racing environments.…”
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A Robust Ensemble Model for Plant Disease Detection Using Deep Learning Architectures by Fida Zubair, Moutaz Saleh, Younes Akbari, Somaya Al Maadeed

“…The proposed approach strategically combines these architectures to leverage their unique strengths: the advanced feature extraction capabilities of InceptionResNetV2, the lightweight and efficient design of MobileNetV2, and the scalable, performance-optimized structure of EfficientNetB3. By integrating these models, the approach aims to improve classification accuracy and robustness and overcome the multiple challenges of plant disease detection. …”
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MPVF: Multi-Modal 3D Object Detection Algorithm with Pointwise and Voxelwise Fusion by Peicheng Shi, Wenchao Wu, Aixi Yang

“…3D object detection plays a pivotal role in achieving accurate environmental perception, particularly in complex traffic scenarios where single-modal detection methods often fail to meet precision requirements. …”
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CDK: A novel high-performance transfer feature technique for early detection of osteoarthritis by Mohammad Shariful Islam, Mohammad Abu Tareq Rony

“…This underscores the need for more advanced diagnostic methods, such as machine learning (ML) and deep learning (DL), to improve OA detection and classification. …”
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Soft detection model of corrosion leakage risk based on KNN and random forest algorithms by Yang YANG, Chengzhi LI, Xuan DU, Xiao YU, Shaohua DONG

“…Objective The integrity management of urban gas pipeline networks demands effective risk assessment methods. Corrosion leakage risk assessment necessitates the comprehensive integration of risk assessment factors with various detection operations. …”
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Rapid and Visual Detection of Mycobacterium tuberculosis Complex Based on Multiplex Recombinase Polymerase Amplification by Xiaoyan Tan, Yongcong Li, Xufu Xiang, Wei Wu, Gang Wang, Sai Zhang

“…M. tuberculosis control was used to optimize the reaction temperature. Additionally, we calculated and compared the limit of detection, specificity, and coincidence rate between this platform and the TaqMan real‐time fluorescence quantification method (RT‐qPCR) using two sets of national reference panels and 10 strains of MTBC. …”
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Loop-mediated isothermal amplification assays for the detection of antimicrobial resistance elements in Vibrio cholera by Daniel Antonio Negrón, Shipra Trivedi, Nicholas Tolli, David Ashford, Gabrielle Melton, Stephanie Guertin, Katharine Jennings, Bryan D. Necciai, Shanmuga Sozhamannan, Bradley W. Abramson

“…Overall, 9 of the 16 tested LAMP assays had positive signal through visual and computer vision-based detection methods developed here. Here we show LAMP assays tested on synthetic AMR gene targets for aph(6), varG, floR, qnrVC5, and almG, which allow for resistance to aminoglycosides, penicillins, carbapenems, phenicols, fluoroquinolones, and polymyxins respectively.…”
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Enhanced neurological anomaly detection in MRI images using deep convolutional neural networks by Ahmed Mateen Buttar, Zubair Shaheen, Abdu H. Gumaei, Mogeeb A. A. Mosleh, Mogeeb A. A. Mosleh, Indrajeet Gupta, Samah M. Alzanin, Muhammad Azeem Akbar

“…This study introduces a deep learning framework designed to automate neuro-diagnostics, addressing the limitations of current manual interpretation methods, which are often time-consuming and prone to variability.MethodsWe propose a specialized deep convolutional neural network (DCNN) framework aimed at detecting and classifying neurological anomalies in MRI data. …”
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DVAEGMM: Dual Variational Autoencoder With Gaussian Mixture Model for Anomaly Detection on Attributed Networks by Wasim Khan, Mohammad Haroon, Ahmad Neyaz Khan, Mohammad Kamrul Hasan, Asif Khan, Umi Asma Mokhtar, Shayla Islam

“…Most current approaches focus on shallow learning methods such as community analysis, ego network or selection of subspace method. …”
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Leveraging large language models for automated detection of velopharyngeal dysfunction in patients with cleft palate by Myranda Uselton Shirk, Catherine Dang, Jaewoo Cho, Hanlin Chen, Lily Hofstetter, Jack Bijur, Claiborne Lucas, Andrew James, Ricardo-Torres Guzman, Andrea Hiller, Noah Alter, Amy Stone, Maria Powell, Matthew E. Pontell, Matthew E. Pontell

“…This study explores the application of OpenAI's Whisper model for automated hypernasality detection, offering a scalable and efficient alternative to traditional approaches.MethodsThe Whisper model was adapted for binary classification by replacing its sequence-to-sequence decoder with a custom classification head. …”
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Enhancing Anomaly Detection Through Latent Space Manipulation in Autoencoders: A Comparative Analysis by Tomasz Walczyna, Damian Jankowski, Zbigniew Piotrowski

“…This study highlights the impact of optimizing parameter configurations, lightweight architectures, and training methodologies to enhance anomaly detection performance. …”
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Flexible Adaptive Marine Predator Algorithm and Its Application in Fault Detection for Wind Turbines by WANG Wen, YI Jiabiao

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