Evaluating YOLO Variants With Transfer Learning for Real-Time UAV Obstacle Detection in Simulated Forest Environments by Shouthiri Partheepan, Farzad Sanati, Jahan Hassan

“…The results offer practical guidance for selecting YOLO architectures in UAV-based obstacle detection tasks, balancing accuracy, speed, and deployment feasibility in complex environments.…”
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Multi-Domain Controversial Text Detection Based on a Machine Learning and Deep Learning Stacked Ensemble by Jiadi Liu, Zhuodong Liu, Qiaoqi Li, Weihao Kong, Xiangyu Li

“…Firstly, considering the multidimensional complexity of textual features, we integrate comprehensive feature engineering, i.e., encompassing word frequency, statistical metrics, sentiment analysis, and comment tree structure features, as well as advanced feature selection methodologies, particularly lassonet, i.e., a neural network with feature sparsity, to effectively address dimensionality challenges while enhancing model interpretability and computational efficiency. …”
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SOFTWARE COMPONENT DEVELOPMENT FOR PARALLEL GATEWAYS DETECTION AND QUALITY ASSESSMENT IN BPMN MODELS USING FUZZY LOGIC by Andrii Kopp, Ľuboš Cibák, Dmytro Orlovskyi, Dmytro Kudii

“…Errors in their implementation, such as incorrect synchronization or termination of parallel branches, are common and difficult to detect by traditional metrics such as the Number of Activities (NOA) or Control-Flow Complexity (CFC). …”
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Improving Fire and Smoke Detection with You Only Look Once 11 and Multi-Scale Convolutional Attention by Yuxuan Li, Lisha Nie, Fangrong Zhou, Yun Liu, Haoyu Fu, Nan Chen, Qinling Dai, Leiguang Wang

“…Although challenges remain in handling occluded targets and complex backgrounds, the model exhibits strong robustness and generalization capabilities, maintaining efficient detection performance in complicated environments.…”
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Optimized Ensemble Deep Learning for Real-Time Intrusion Detection on Resource-Constrained Raspberry Pi Devices by Muhammad Bisri Musthafa, Samsul Huda, Tuy Tan Nguyen, Yuta Kodera, Yasuyuki Nogami

“…Deep learning techniques offer promising solutions for such detection due to their superior complex pattern recognition and anomaly detection capabilities in large datasets. …”
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TCCDNet: A Multimodal Pedestrian Detection Network Integrating Cross-Modal Complementarity with Deep Feature Fusion by Shipeng Han, Chaowen Chai, Min Hu, Yanni Wang, Teng Jiao, Jianqi Wang, Hao Lv

“…Multimodal pedestrian detection has garnered significant attention due to its potential applications in complex scenarios. …”
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Hierarchical Attention Module-Based Hotspot Detection in Wafer Fabrication Using Convolutional Neural Network Model by Mobeen Shahroz, Mudasir Ali, Alishba Tahir, Henry Fabian Gongora, Carlos Uc Rios, Md Abdus Samad, Imran Ashraf

“…As integrated circuits continue to grow in complexity, doing efficient yield analyses is becoming more essential but also more difficult. …”
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DDoSNet: Detection and prediction of DDoS attacks from realistic multidimensional dataset in IoT network environment by Goda Srinivasa Rao, P. Santosh Kumar Patra, V.A. Narayana, Avala Raji Reddy, G.N.V. Vibhav Reddy, D. Eshwar

“…The Internet of Things (IoT) network infrastructures are becoming more susceptible to distributed denial of service (DDoS) attacks because of the proliferation of IoT devices. Detecting and predicting such attacks in this complex and dynamic environment requires specialized techniques. …”
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HPRT-DETR: A High-Precision Real-Time Object Detection Algorithm for Intelligent Driving Vehicles by Xiaona Song, Bin Fan, Haichao Liu, Lijun Wang, Jinxing Niu

“…This integration expands the model’s receptive field and enhances feature extraction without adding learnable parameters or complex computations, effectively minimizing missed detections of small targets. …”
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Fast Anomaly Detection for Vision-Based Industrial Inspection Using Cascades of Null Subspace PCA Detectors by Muhammad Bilal, Muhammad Shehzad Hanif

“…In this study, we introduce a novel anomaly detection framework that leverages feature maps from a lightweight convolutional neural network (CNN) backbone, MobileNetV2, and cascaded detection to achieve notable accuracy as well as computational efficiency. …”
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MonoDFM: Density Field Modeling-Based End-to-End Monocular 3D Object Detection by Gang Liu, Xinrui Huang, Xiaoxiao Xie

“…Moreover, compared with more complex approaches like Neural Radiance Fields (NeRF), MonoDFM provides a streamlined and efficient prediction process. …”
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YS3AM: Adaptive 3D Reconstruction and Harvesting Target Detection for Clustered Green Asparagus by Si Mu, Jian Liu, Ping Zhang, Jin Yuan, Xuemei Liu

“…Extracting precise stem details in complex spatial arrangements is a challenge. This paper explored the YS3AM (Yolo-SAM-3D-Adaptive-Modeling) method for detecting green asparagus and performing 3D adaptive-section modeling using a depth camera, which could benefit harvesting path planning for selective harvesting robots. …”
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DSAT: a dynamic sparse attention transformer for steel surface defect detection with hierarchical feature fusion by Shouluan Wu, Hui Yang, Liefa Liao, Chao Song, Yating Fang, Jianglong Fu, Tan Li

“…These defects exhibit diverse morphological characteristics and complex patterns, which pose substantial challenges to traditional detection models, particularly regarding multi-scale feature extraction and information retention across network depths. …”
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LCCDMamba: Visual State Space Model for Land Cover Change Detection of VHR Remote Sensing Images by Junqing Huang, Xiaochen Yuan, Chan-Tong Lam, Yapeng Wang, Min Xia

“…Recently, with the advent of Mamba, which maintains linear time complexity and high efficiency in processing long-range data, it offers a new solution to address feature-fusion challenges in LCCD. …”
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Enhanced diabetic retinopathy detection using U-shaped network and capsule network-driven deep learning by Govindharaj I, Poongodai A, Gnanajeyaraman Rajaram, Santhakumar D, Ravichandran S, Vijaya Prabhu R, Udayakumar K, Yazhinian S

“…Glaucoma, a severe eye disease leading to irreversible vision loss if untreated, remains a significant challenge in healthcare due to the complexity of its detection. Traditional methods rely on clinical examinations of fundus images, assessing features like optic cup and disc sizes, rim thickness, and other ocular deformities. …”
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Optimization and Validation of Universal Real-Time RT-PCR Assay to Detect Virulent Newcastle Disease Viruses by Ellen Ruth Alexander Morris, Megan E. Schroeder, Phelue N. Anderson, Lisa J. Schroeder, Nicholas Monday, Gabriel Senties-Cue, Martin Ficken, Pamela J. Ferro, David L. Suarez, Kiril M. Dimitrov

“…The considerable genetic diversity of the virus adds complexity to maintaining the high sensitivity and specificity of molecular detection assays. …”
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Development of eco-friendly and cost-effective electrochemical sensor for the simultaneous detection of 4-aminophenol and paracetamol in water by Antía Fdez-Sanromán, Najib Ben Messaoud, Marta Pazos, Emilio Rosales, Raquel Barbosa Queirós

“…It was successfully tested in real freshwater samples, demonstrating high accuracy even in complex matrices. This innovative methodology provides a rapid, cost-effective, and portable analytical tool for routine monitoring of pharmaceutical contaminants, enabling more accurate environmental risk assessments and supporting the implementation of more efficient management strategies.…”
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ASIC Design for Real-Time CAN-Bus Intrusion Detection and Prevention System Using Random Forest by Junseok Lee, Sangmin Park, Sua Shin, Hyungchul Im, Joosock Lee, Seongsoo Lee

“…To address this issue, we designed an IDS that can immediately determine if an attack is present when receiving a CAN frame and blocking the attack node. Fast and efficient detection is possible complex matrix operations because the random forest model performs detection based on comparison operations. …”
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Blockchain enabled deep learning model with modified coati optimization for sustainable healthcare disease detection and classification by Heba G. Mohamed, Fadwa Alrowais, Fahd N. Al-Wesabi, Mesfer Al Duhayyim, Anwer Mustafa Hilal, Abdelwahed Motwakel

“…The presented MCOBC-HDDC method provides an efficient and accurate disease diagnosis, utilizing a system that depends on DL techniques. …”
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Design of an Improved Model for Anomaly Detection in CCTV Systems Using Multimodal Fusion and Attention-Based Networks by V. Srilakshmi, Sai Babu Veesam, Mallu Shiva Rama Krishna, Ravi Kumar Munaganuri, Dulam Devee Sivaprasad

“…Long Short-Term Memory (LSTM) can capture long-range dependencies in sequential data, while Temporal Convolutional Network (TCN) efficiently models temporal patterns using convolutional layers and Transformer Networks fathom the relative importance of temporal features against one another through self-attention, thus improving their detection accuracy for anomalies that happen over a long duration. …”
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