ASD-YOLO: a lightweight network for coffee fruit ripening detection in complex scenarios by Baofeng Ye, Baofeng Ye, Renzheng Xue, Renzheng Xue, Haiqiang Xu, Haiqiang Xu

“…In order to improve the detection efficiency of coffee fruit maturity, this paper proposes an improved detection method based on YOLOV7 to efficiently identify the maturity of coffee fruits, called ASD-YOLO. …”
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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

“…The hyperparameters of our model are tuned by utilizing those selected features to maximize the accuracy. The model developed is verified using three different datasets, which have been widely applied to intrusion detection. …”
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Selective trimerization of ethylene using chromium catalysts complexed with tridentate ligands supported on titanium modified silica by Younes Habibi, Mohamadreza Marefat, Sajjad Gharajedaghi, Masoumeh Mohamadhoseini, Zahra Mohamadnia, Ebrahim Ahmadi

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REDETR-RISTD: Real-Time Long-Range Infrared Small Target Detection Network Based on the Reparameterized Efficient Detection Transformer by Ning Li, Daozhi Wei

“…This happens because the targets are small in size, have a weak signal-to-noise ratio (SNR), and are surrounded by complex backgrounds. A novel real-time long-range infrared small target detection network based on the Reparameterized Efficient Detection Transformer (REDETR-RISTD) is proposed. …”
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Low complexity hybrid iterative algorithm based signal detection in massive MIMO system by Shufeng ZHAO, Bin SHEN, Furong YANG

“…Among the uplink signal detection algorithms for massive MIMO systems,the minimum mean square error (MMSE) algorithm can achieve the near-optimal linear detection performance.However,conventional MMSE usually involves high complexity due to the required matrix inversion of large-size matrix,which makes it hard to implement in realistic applications.Based on joint steepest descent (SD) algorithm and Gauss-Seidel iteration,a low complexity hybrid iterative detection algorithm was proposed.The SD algorithm was employed to obtain an efficient searching direction for the following Gauss-Seidel to speed up convergence.Meanwhile,an approximated method was also proposed to compute the bit log-likelihood ratio (LLR) for soft channel decoding.Simulation results verify that the proposed algorithm can converge rapidly and achieve its performance quite close to that of the MMSE algorithm with only a small number of iterations.Meanwhile,the complexity is reduced by an order of magnitude,which is kept consistently of O(K ²).…”
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Nearest neighbor permutation entropy detects phase transitions in complex high-pressure systems by Arthur A. B. Pessa, Leonardo G. J. M. Voltarelli, Lúcio Cardozo-Filho, Andres G. M. Tamara, Claudio Dariva, Papa M. Ndiaye, Matjaž Perc, Haroldo V. Ribeiro

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On the Design of Near-Optimal Generalized Block-Based Spatial Modulation With Low Detection Complexity by Yen-Ming Chen, Wei-Lun Lin, Heng Lee, Tsung-Lin Chen

“…However, independently designing the constellation cardinality and TACs leads to limited performance gains and an exponential increase in complexity, particularly under maximum-likelihood (ML) detection. …”
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Specific and Rapid Detection of Mycobacterium tuberculosis Complex in Clinical Samples by Polymerase Chain Reaction by Anamika Singh, Vijendra Kumar Kashyap

“…This method, by well distinguishing between MTB complex and NTM, presented a fast and accurate method to detect and diagnose mycobacterial infections more efficiently and could thereby help in better patient management particularly considering the increase in mycobacterial infections due to emergence of NTM over the past decades.…”
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A Precise Detection Method for Tomato Fruit Ripeness and Picking Points in Complex Environments by Xinfa Wang, Xuan Wen, Yi Li, Chenfan Du, Duokuo Zhang, Chengxiu Sun, Bihua Chen

“…Aiming at the problems faced in practical applications, such as low accuracy of tomato ripeness and picking points detection in complex greenhouse environments, which leads to wrong picking, missed picking, and fruit damage by robots, this study proposes the YOLO-TMPPD (Tomato Maturity and Picking Point Detection) model. …”
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The Method of Selecting Boiler Houses under Technical Re-Equipment in a Mini-CHP by Myshkina L.S., Frolova Y.A., Ivanova E.M.

“…The significance of the results lies in the fact that the proposed methodology makes it possible to increase the validity of decisions when transforming a boiler house into a mini-CHPP. The use of the selection results will lead to an increase in the economic efficiency of the heat supply system. …”
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Research on Vehicle Target Detection Method Based on Improved YOLOv8 by Mengchen Zhang, Zhenyou Zhang

“…To improve the performance of vehicle target detection in complex traffic environments and solve the problem that it is difficult to make a lightweight detection model, this paper proposes a lightweight vehicle detection model based on enhanced You Only Look Once v8. …”
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Robust face mask detection in complex scenarios using YOLOv8 and context-aware convolutions by Yingjie Wei, Huili Li, Yuanfei He, Li Li, Qiongshuai Lyu, Yu Yang

“…Abstract Aiming to address the challenges of reduced detection accuracy in face mask applications due to mutual occlusion, lighting variations, and detection distance, this paper proposes a face mask detection algorithm tailored for complex environments. …”
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Optimizing Input Selection for Cardiac Model Training and Inference: An Efficient 3D Convolutional Neural Networks-Based Approach to Automate Coronary Angiogram Video Selection by Shih-Sheng Chang, MD, PhD, Behrouz Rostami, PhD, Gerardo LoRusso, MD, Chia-Hao Liu, MD, Mohamad Alkhouli, MD

“…Objective: To develop an efficient and automated method for selecting appropriate coronary angiography videos for training deep learning models, thereby improving the accuracy and efficiency of medical image analysis. …”
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Enhancing credit card fraud detection: highly imbalanced data case by Dalia Breskuvienė, Gintautas Dzemyda

“…This paper emphasizes the main issues in fraud detection and suggests a novel feature selection method called FID-SOM (feature selection for imbalanced data using SOM). …”
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Dual-stage feature specialization network for robust visual object detection in autonomous vehicles by Ze Liu, Junhua Wu, Yingfeng Cai, Hai Wang, Long Chen, Qingchao Liu

“…Existing two-stage object detection methods often suffer from feature interference between candidate region generation and classification regression tasks, leading to suboptimal performance in complex scenes. …”
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Algorithm for Selection Equipment to Reduce the Technogenic Effect on the Environment by Kozii I.S., Plyatsuk L.D., Koval V.V.

“…The work is devoted to the development of an algorithm for selection dust and gas purification equipment in order to reduce the anthropogenic impact on the environment from emissions of the heat, power and chemical industries, which are sources of complex environmental pollution. …”
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MEIS-YOLO: Improving YOLOv11 for efficient aerial object detection with lightweight design by Yicheng Liu, Jinsong Wu, Li Chen

“…The core innovation of the model lies in the introduction of a Multi-scale Edge Information Selection (MEIS) module, which selects key features highly relevant to the target detection task from multi-scale features, strengthening the representation of edge information and significantly improving detection performance under conditions of small targets and complex backgrounds. …”
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Evaluating YOLO Models for Efficient Crack Detection in Concrete Structures Using Transfer Learning by Muhammad Sohaib, Muzamal Arif, Jong-Myon Kim

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A secure and efficient deep learning-based intrusion detection framework for the internet of vehicles by Hasim Khan, Ghanshyam G. Tejani, Rayed AlGhamdi, Sultan Alasmari, Naveen Kumar Sharma, Sunil Kumar Sharma

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An EfficientNetv2-based method for coal conveyor belt foreign object detection by Tao Hu, Deyu Zhuang, Jinbo Qiu

“…This article proposes a foreign object detection method for coal conveyor belts based on EfficientNetv2. …”
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