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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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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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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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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A Lightweight Cotton Field Weed Detection Model Enhanced with EfficientNet and Attention Mechanisms by Lu Zheng, Lyujia Long, Chengao Zhu, Mengmeng Jia, Pingting Chen, Jun Tie

“…The model leverages EfficientNet to reconstruct the backbone, reducing model complexity and enhancing detection speed. …”
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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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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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A Refined and Efficient CNN Algorithm for Remote Sensing Object Detection by Bingqi Liu, Peijun Mo, Shengzhe Wang, Yuyong Cui, Zhongjian Wu

“…RE_CSP block efficiently extracts multi-scale information, overcoming challenges posed by complex backgrounds. …”
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Enhanced Lightweight YOLO Model for Efficient Vehicle Detection in Satellite Imagery by Mohamad Haniff Junos, Anis Salwa Mohd Khairuddin, Elmi Abu Bakar, Ahmad Faizul Hawary

“…Vehicle detection in satellite images is a challenging task due to the variability in scale and resolution, complex background, and variability in object appearance. …”
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An efficient network for object detection in scale-imbalanced remote sensing images by Li Zhongyu, Jing Xiaoping, Sun Rui, Yang Yazhi, Wang Wei, Zhu Hongzhen

“…The model first introduces an improved frequency channel attention mechanism to design a feature extraction module to improve the extraction of key features by the neural network; second, considering that the complete intersection over union method does not comprehensively consider the aspect ratio of the bounding box, which will cause the loss of small-scale target feature information, the efficient intersection over union method is used to improve it; then, because of the high missed detection rate of the non-maximum suppression (NMS) method, Soft-EIoU-NMS is used to replace the original NMS method. …”
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A DFT insight into the potential of cycloparaphenylenes as efficient sensors for detecting Paracetamol by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

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RADNet: Adaptive Spatial-Dilation Learning for Efficient Road Crack Detection by Kehao Du, Yifan Dai

“…Road crack detection is crucial for infrastructure maintenance and traffic safety, yet existing methods struggle to balance detection accuracy and computational efficiency due to complex texture similarities between cracks and road surfaces. …”
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Angus: efficient active learning strategies for provenance based intrusion detection by Lin Wu, Yulai Xie, Jin Li, Dan Feng, Jinyuan Liang, Yafeng Wu

“…Besides, we also improve the above query strategies by using the parallel query to reduce detection time overheads. The experiments on various real-world applications demonstrate their performance and efficiency.…”
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ELNet: An Efficient and Lightweight Network for Small Object Detection in UAV Imagery by Hui Li, Jianbo Ma, Jianlin Zhang

“…In addition, since YOLOv12n employs standard convolution for downsampling, which is inefficient for extracting UAV image features, we design a novel downsampling module, EDown, to further reduce model size and enable more efficient feature extraction. Finally, to improve detection in UAV imagery with dense, small, and scale-varying objects, we propose DIMB-C3k2, an enhanced module built upon C3k2, which boosts feature extraction under complex conditions. …”
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PEYOLO a perception efficient network for multiscale surface defects detection by Xun Li, Yuzhen Zhao, Xiangke Jiao, Qingzhe Meng, Zhun Guo, Ruijuan Yao, Yaqiao Yang, Baoxi Yuan

“…To address this issue, we propose an innovative perception-efficient network designed for the fast and accurate detection of multi-scale surface defects. …”
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EcoDetect-YOLOv2: A High-Performance Model for Multi-Scale Waste Detection in Complex Surveillance Environments by Jing Su, Ruihan Chen, Mingzhi Li, Shenlin Liu, Guobao Xu, Zanhong Zheng

“…Even with surveillance imagery, challenges such as cluttered backgrounds, scale variation, and small object sizes often lead to missed detections and reduced robustness. To address these challenges, this study introduces EcoDetect-YOLOv2, a lightweight and high-efficiency object detection model developed using the Intricate Environment Waste Exposure Detection (IEWED) dataset. …”
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Streamlining Deep Learning Network for Real-time Sea Turtle Detection by Muhamad Dwisnanto Putro, Yuliana Mose, Alex Copernikus Andaria, Jane Litouw, Vecky Canisius Poekoel, Xaverius Najoan

“…A new turtle dataset is proposed that contains lighting, blur, occlusion, and complex background challenges. The evaluation results show that the proposed model performs higher accuracy than other lightweight object detection models. …”
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Utilizing an Enhanced YOLOv8 Model for Fishery Detection by Hanyu Jiang, Jiacheng Zhong, Fuyu Ma, Cheng Wang, Ruiwen Yi

“…The results demonstrate that our method provides an efficient and reliable automatic detection technology for precision underwater fishing.…”
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Flexi-YOLO: A lightweight method for road crack detection in complex environments. by Jiexiang Yang, Renjie Tian, Zexing Zhou, Xingyue Tan, Pingyang He

“…Road crack detection is critical to global infrastructure maintenance and public safety, and complex background environments and nonlinear damage crack patterns challenge the need for real-time, efficient, and accurate detection.This paper proposes a lightweight yet robust Flexi-YOLO model based on the YOLOv8 algorithm. …”
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