Personalizing Seizure Detection for Individual Patients by Optimal Selection of EEG Signals by Rosanna Ferrara, Martino Giaquinto, Gennaro Percannella, Leonardo Rundo, Alessia Saggese

“…The proposed approach ensures high reliability, even with small datasets, and improves interpretability for clinicians by overcoming the limitations of more complex methods. The tailored channel selection boosts detection accuracy and ensures robust performance across different seizure types while reducing the computational burden typical of multi-electrode systems. …”
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Image-based maturity detection for selective cauliflower harvesting in field condition by Ajay Kushwah, P.K. Sharma, H.L. Kushwaha, Brij Bihari Sharma, Naseeb Singh, Ramineni Harsha Nag, Manojit Chowdhury, Nrusingh Charan Pradhan, Gopal Carpenter, Silpa Mandal, Ali Salem

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Enhancing the efficiency of the use of complex pathomorphological studies for the timely diagnostics of mycosis fungoides by N. V. Kungurov, G. D. Safonova, M. M. Kokhan, O. G. Rimar, I. A. Kuklin

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Small Target Detection for Power Line Components in Complex UAV Imagery by Zhiyuan Sun, Xu Wang

“…To address the limitations of existing algorithms—particularly their low efficiency in detecting small objects and poor accuracy in complex backgrounds—we propose a defect detection model for transmission line components based on YOLOv5. …”
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Balancing complexity and accuracy for defect detection on filters with an improved RT-DETR by Maoyuan Zhang, Xiaojuan Wei, Guojun Liu, Mengxu Chen, Chunxia Zhao, Yingxiao Liu, Zhikang Bao, Yunfeng Guo, Run An, Pengcheng Zhao

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MRD: A Linear-Complexity Encoder for Real-Time Vehicle Detection by Kaijie Li, Xiaoci Huang

“…To address these limitations, this study introduces Mamba RT-DETR (MRD), an optimized architecture featuring three principal innovations: (1) We devise an efficient vehicle detection Mamba (EVDMamba) network that strategically integrates a linear-complexity state space model (SSM) to substantially mitigate computational overhead while preserving feature extraction efficacy. (2) To counteract the constrained receptive fields and suboptimal spatial localization associated with conventional SSM sequence modeling, we implement a multi-branch collaborative learning framework that synergistically optimizes channel dimension processing, thereby augmenting the model’s capacity to capture critical spatial dependencies. (3) Comprehensive evaluations on the BDD100K benchmark demonstrate that MRD architecture achieves a 3.1% enhancement in mean average precision (mAP) relative to state-of-the-art RT-DETR variants, while concurrently reducing parameter count by 55.7%—a dual optimization of accuracy and efficiency.…”
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Low Complexity Optimized AOR Method for Massive MIMO Signal Detection by Muhammad Nauman Irshad, Muhamamd Muzamil Aslam, Rardchawadee Silapunt

“…Simulation results of the proposed method indicate superior performance compared to existing techniques in detection accuracy, error rates, and reduced computational complexity.…”
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Reduced-Complexity Radio Architectures for Enhanced Receive Selection Combining in Multiuser Diversity Systems by Elpiniki P. Tsakalaki, Osama N. Alrabadi, Constantinos B. Papadias, Ramjee Prasad

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Insulator Defect Detection in Complex Environments Based on Improved YOLOv8 by Yuxin Qin, Ying Zeng, Xin Wang

“…To solve the problems of its low accuracy, high delay, and large model size in complex environments, following the principle of progressive extraction from high-entropy details to low-entropy semantics, an improved YOLOv8 target detection network for insulator defects based on bidirectional weighted feature fusion was proposed. …”
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YOLO-SAATD: An efficient SAR airport and aircraft target detector by Daobin Ma, Zhanhong Lu, Zixuan Dai, Yangyue Wei, Li Yang, Haimiao Hu, Wenqiao Zhang, Dongping Zhang

“…While object detection performs well in natural images, it faces challenges in Synthetic Aperture Radar (SAR) images for detecting airports and aircraft due to discrete scattering points, complex backgrounds, and multi-scale targets. …”
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Reducing PAPR in NOMA Waveforms Using Genetic-Enhanced PTS and SLM: A Low-Complexity Approach for Improved throughput, power spectral density, and Power Efficiency by Arun Kumar, Nishant Gaur, Aziz Nanthaamornphong

“…To overcome these issues, this paper introduces new Particle Swarm Optimization (PSO)-improved partial transmit sequence (PTS) and Selective Mapping (SLM) schemes that optimally choose phase factors with much lower search complexity. …”
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INDICATORS AND CRITERIA FOR ASSESSMENT OF MULTIFUNCTIONAL DEVELOPMENT OF RURAL TERRITORIES by O. V. Kosenchuk, A. V. Zinich

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Reliability and Quality of Complex Systems by D.N. Novomeisky, M.N. Piganov, E.T. Eskibaev

An efficient fire detection algorithm based on Mamba space state linear attention by Yuming Li, Yongjie Wang, Xiaorui Shao, Anbo Zheng

“…Abstract As an emerging State Space Model (SSM), the Mamba model draws inspiration from the architecture of Recurrent Neural Networks (RNNs), significantly enhancing the global receptive field and feature extraction capabilities of object detection models. Compared to traditional Convolutional Neural Networks (CNNs) and Transformers, Mamba demonstrates superior performance in handling complex scale variations and multi-view interference, making it particularly suitable for object detection tasks in dynamic environments such as in fire detection scenarios. …”
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MATHEMATICAL MODEL OF COMPLEX PROTECTION OF AN INFOCOMMUNICATION OBJECT BASED ON "PLAYING WITH NATURE" by I. S. Klimenko

“…The algorithm of formalization of protection processes is proposed, which ensures efficient use of resources when detecting possible incidents of violation of the protection system and/or unauthorized access. …”
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Multiple model visual feature embedding and selection method for an efficient ocular disease classification by Isha Kansal, Vikas Khullar, Preeti Sharma, Supreet Singh, Junainah Abd Hamid, A. Johnson Santhosh

“…Abstract Early detection of ocular diseases is vital to preventing severe complications, yet it remains challenging due to the need for skilled specialists, complex imaging processes, and limited resources. …”
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SkinEHDLF a hybrid deep learning approach for accurate skin cancer classification in complex systems by Umesh Kumar Lilhore, Yogesh Kumar Sharma, Sarita Simaiya, Roobaea Alroobaea, Abdullah M. Baqasah, Majed Alsafyani, Afnan Alhazmi

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Hybrid metaheuristic optimization for detecting and diagnosing noncommunicable diseases by Saleem Malik, S. Gopal Krishna Patro, Chandrakanta Mahanty, Saravanapriya Kumar, Ayodele Lasisi, Quadri Noorulhasan Naveed, Anjanabhargavi Kulkarni, Abdulrajak Buradi, Addisu Frinjo Emma, Naoufel Kraiem

“…These algorithms aim to address the challenges of feature selection, computational complexity, and disease classification accuracy. …”
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An Efficient Deep Learning Approach for Malaria Parasite Detection in Microscopic Images by Sorio Boit, Rajvardhan Patil

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LMD_YOLO: A Lightweight and Efficient Model for Pavement Defects Detection by Shuai He, Ye Yuan, Bingyang Yin

“…These advancements enable LMD_YOLO to achieve high detection accuracy and robustness in complex conditions while maintaining computational efficiency. …”
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