TW-YOLO: An Innovative Blood Cell Detection Model Based on Multi-Scale Feature Fusion by Dingming Zhang, Yangcheng Bu, Qiaohong Chen, Shengbo Cai, Yichi Zhang

“…However, due to the diversity and complexity of blood cell images, traditional models still exhibit deficiencies in blood cell detection. …”
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FastADnet: Fast Anomaly Detection via Core-Feature Centered Cluster Reconstruction Network by Daeyeob Na, Youngjoon Yoo

“…In recent works in this field, there are trade-offs between computational complexity and anomaly detection accuracy for effective deployment. …”
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Multimodal AI-driven object detection with uncertainty quantification for cardiovascular risk assessment in autistic patients by Ling Tang, Chengchao Shen

“…IntroductionArtificial Intelligence (AI) has transformed medical diagnostics, offering enhanced precision and efficiency in detecting cardiovascular risks. However, traditional diagnostic approaches for cardiovascular risk assessment in autistic patients remain limited due to the complexity of medical data, inter-individual variability, and the challenges of integrating multi-modal clinical information. …”
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Arbitrarily Oriented Object Detection in Remote Sensing Images Based on Improved YOLOv4-CSP by Ziyang Zheng, Ting Zhang, Zhaoying Liu, Bo Liu, Yujian Li, Changming Sun

“…In order to further improve the detection accuracy and provide a more efficient model for scenes that require real-time detection, we propose an improved YOLOv4-CSP network for rotating object detection in remote sensing images. …”
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MT-CMVAD: A Multi-Modal Transformer Framework for Cross-Modal Video Anomaly Detection by Hantao Ding, Shengfeng Lou, Hairong Ye, Yanbing Chen

“…Our optimized window-shift attention mechanism also reduces computational complexity, making MT-CMVAD a robust and efficient solution for safety-critical video understanding tasks.…”
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Beyond the Grid: GLRT-Based TomoSAR Fast Detection for Retrieving Height and Thermal Dilation by Nabil Haddad, Karima Hadj-Rabah, Alessandra Budillon, Gilda Schirinzi

“…While effective, these methods face two primary limitations: high computational complexity and the off-grid problem caused by the discretization of the search space. …”
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An Attention-Enhanced 3D-CNN Framework for Spectrogram-Based EEG Analysis in Epilepsy Detection by Ziaullah Khan, Aakanksha Dayal, Hee-Cheol Kim

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Supervised Anomaly Detection in Univariate Time-Series Using 1D Convolutional Siamese Networks by Ayan Chatterjee, Vajira Thambawita, Michael A. Riegler, Pal Halvorsen

“…Anomalies can compromise data quality and operational efficiency. The complexity of time-series data, with its temporal dependencies and potential non-stationarity, makes anomaly detection challenging but essential. …”
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AH-YOLO: An Improved YOLOv8-Based Lightweight Model for Fire Detection in Aircraft Hangars by Li Deng, Zhuoyu Wang, Quanyi Liu

“…First, the MobileOne module is integrated to reduce the network complexity and improve the computational efficiency. …”
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Effects of Broken Rotor Bars on Three-Phase Induction Machines and Detection Methods – State of Arts by Boudmane Bilal, Rachid Aziz, Mortabit Idriss, Errifai Nidale

“…Identifying and addressing rotor bar issues promptly is crucial for maintaining operational reliability and minimizing unplanned maintenance activities. Detecting broken rotor bars presents challenges due to the subtle nature of early-stage faults and the complexity of motor operating conditions. …”
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A Blockchain-Based Federated Forest for SDN-Enabled In-Vehicle Network Intrusion Detection System by Ibrahim Aliyu, Marco Carlo Feliciano, Selinde Van Engelenburg, Dong Ok Kim, Chang Gyoon Lim

“…We found that the proposed system has efficient use of memory and CPU resources and that the detection rate of closely related attacks was high. …”
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Radar Coherent Detection for Maneuvering Target Based on Product-Scaled Integrated Cubic Phase Function by Jinyang Chen, Ke Jin, Shangjiang Yu, Tao Lai, Yongjun Zhao

“…Analysis demonstrates that the SNUFFT has the same computational complexity with nonuniform fast Fourier transform (NUFFT), and thus the PSICPF could be efficiently implemented via complex multiplications, the fast Fourier transform (FFT), and NUFFT. …”
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A security data detection and management method in digital library network based on deep learning by Diyin Zhu, Yihang Wei, Jiali Cai, Jingwen Wang, Zhongshan Chen

“…It efficiently and intelligently detects and manages security data in digital library network. …”
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Object Detection in High-Resolution UAV Aerial Remote Sensing Images of Blueberry Canopy Fruits by Yun Zhao, Yang Li, Xing Xu

“…We also introduced a non-maximal suppression algorithm, Cluster-NMF, which accelerates inference speed through matrix parallel computation and merges multiple high-quality target detection frames to generate an optimal detection frame, enhancing the efficiency of blueberry canopy fruit detection without compromising inference speed.…”
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Fast real-time detection and counting of thrips in greenhouses with multi-level feature attention and fusion by Zhangzhang He, Xinyue Chen, Ying Gao, Yu Zhang, Yuheng Guo, Tong Zhai, Xiaochen Wei, Huan Li, Haipeng Zhu, Yongkun Fu, Zhiliang Zhang, Zhiliang Zhang

“…Compared to existing methods, TCD-Net achieves higher thrips counting and detection accuracy with lower computational complexity. …”
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Adaptive Fuzzy C-Means with logit boost distributed clustering for cancer detection with protein sequences by K. Thenmozhi, M. Pyingkodi, V. S. Prakash, Kripa Josten, S. Manju Priya, J. Vennila

“…Abstract The Adaptive Fuzzy C-Means with Logit Boost Distributed Clustering (AFC-LBDC) technique is introduced to enhance cancer detection promptly. The various conventional techniques often struggle to improve cancer detection due to their high complexity effectively. …”
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State-of-the-Art Methodologies for Self-Fault Detection, Diagnosis and Evaluation (FDDE) in Residential Heat Pumps by Francesco Pelella, Adelso Flaviano Passarelli, Belén Llopis-Mengual, Luca Viscito, Emilio Navarro-Peris, Alfonso William Mauro

“…The complexity and added value of these tools grow as they progress from simple fault detection to quantitative fault evaluation, enabling more accurate and timely maintenance strategies. …”
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Intrusion detection system based on machine learning using least square support vector machine by Pratik Waghmode, Manideep Kanumuri, Hosam El-Ocla, Tanner Boyle

“…Unauthorized access or attack can be avoided in critical systems using a comprehensive approach via an effective intrusion detection system (IDS). Traditional intrusion detection techniques are no longer accurate and effective enough to handle the demands of the big data age. …”
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Enhancing automated detection and classification of dementia in individuals with cognitive impairment using artificial intelligence techniques by Shoayee Dlaim Alotaibi, Abeer A. K. Alharbi

“…Next, the EADCD-TIPAIT technique performs a binary greylag goose optimization (BGGO)-based feature selection approach to efficiently identify relevant features that distinguish between normal and dementia-affected brain regions. …”
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Infrared Small Target Detection Based on Compound Eye Structural Feature Weighting and Regularized Tensor by Linhan Li, Xiaoyu Wang, Shijing Hao, Yang Yu, Sili Gao, Juan Yue

“…Furthermore, to improve detection speed, the structural tensor of the effective imaging region in infrared compound eye images is reconstructed, and the Representative Coefficient Total Variation method is employed to avoid complex singular value decomposition and regularization optimization computations. …”
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