Deep Learning-Based Data-Assisted Channel Estimation and Detection by Hamidreza Hashempoor, Wan Choi

“…Our Denoising Block also enables direct data detection, rendering the system well-suited for low-latency applications. …”
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SRM-YOLO for Small Object Detection in Remote Sensing Images by Bin Yao, Chengkun Zhang, Qingxiang Meng, Xiandong Sun, Xuyang Hu, Lu Wang, Xilai Li

“…Small object detection presents significant challenges in computer vision, often affected by factors such as low resolution, dense object distribution, and complex backgrounds, which can lead to false positives or missed detections. …”
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Robust Symbol Detection in Large-Scale Overloaded NOMA Systems by Hiroki Iimori, Giuseppe Thadeu Freitas De Abreu, Takanori Hara, Koji Ishibashi, Razvan-Andrei Stoica, David Gonzalez G., Osvaldo Gonsa

“…We a framework for the design of low-complexity and high-performance receivers for multidimensional overloaded non-orthogonal multiple access (NOMA) systems. …”
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Research Progress on Non-destructive Detection Techniques for Potatoes Quality by YANG Guang-hui, LI Hong-ling, ZHANG Hua, LI Hui, LIU Xiao-long, JIA Shang-yun, HU Bo, SHANG Yi-bo

“…Aiming at the problems of traditional manual potato quality classification, such as high labor intensity, low efficiency, easy to cause secondary damage, and inability to judge internal quality, this article elaborated on the research progress of domestic and foreign hyperspectral detection technology, near-infrared spectroscopy detection technology, machine vision detection technology, and ultrasonic detection technology in the application of internal and external quality detection of potatoes. …”
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Detection of Wild Mushrooms Using Machine Learning and Computer Vision by Christos Chaschatzis, Chrysoula Karaiskou, Chryssanthi Iakovidou, Panagiotis Radoglou-Grammatikis, Stamatia Bibi, Sotirios K. Goudos, Panagiotis G. Sarigiannidis

“…The proposed approach utilises unmanned aerial vehicles (UAVs) equipped with multispectral imaging and the YOLOv5 object detection algorithm. A custom dataset, the wild mushroom detection dataset (WOES), comprising 907 annotated aerial and ground images, was developed to support model training and evaluation. …”
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Advances in Object Detection and Localization Techniques for Fruit Harvesting Robots by Xiaojie Shi, Shaowei Wang, Bo Zhang, Xinbing Ding, Peng Qi, Huixing Qu, Ning Li, Jie Wu, Huawei Yang

“…Because of its low recognition accuracy, slow recognition speed and poor localization accuracy, the traditional algorithm cannot meet the requirements of automatic-harvesting robots. …”
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Hard-coded backdoor detection method based on semantic conflict by Anxiang HU, Da XIAO, Shichen GUO, Shengli LIU

“…The current router security issues focus on the mining and utilization of memory-type vulnerabilities, but there is low interest in detecting backdoors.Hard-coded backdoor is one of the most common backdoors, which is simple and convenient to set up and can be implemented with only a small amount of code.However, it is difficult to be discovered and often causes serious safety hazard and economic loss.The triggering process of hard-coded backdoor is inseparable from string comparison functions.Therefore, the detection of hard-coded backdoors relies on string comparison functions, which are mainly divided into static analysis method and symbolic execution method.The former has a high degree of automation, but has a high false positive rate and poor detection results.The latter has a high accuracy rate, but cannot automate large-scale detection of firmware, and faces the problem of path explosion or even unable to constrain solution.Aiming at the above problems, a hard-coded backdoor detection algorithm based on string text semantic conflict (Stect) was proposed since static analysis and the think of stain analysis.Stect started from the commonly used string comparison functions, combined with the characteristics of MIPS and ARM architectures, and extracted a set of paths with the same start and end nodes using function call relationships, control flow graphs, and branching selection dependent strings.If the strings in the successfully verified set of paths have semantic conflict, it means that there is a hard-coded backdoor in the router firmware.In order to evaluate the detection effect of Stect, 1 074 collected device images were tested and compared with other backdoor detection methods.Experimental results show that Stect has a better detection effect compared with existing backdoor detection methods including Costin and Stringer: 8 hard-coded backdoor images detected from image data set, and the recall rate reached 88.89%.…”
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Improved YOLOv5: Efficient Object Detection for Fire Images by Dongxing Yu, Shuchao Li, Zhongze Zhang, Xin Liu, Wei Ding, Xinyi Zhao

“…After training and testing in fire detection instances, the default versions of the YOLO technique exhibit a significantly low level of accuracy. …”
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Broiler Behavior Detection and Tracking Method Based on Lightweight Transformer by Haixia Qi, Zihong Chen, Guangsheng Liang, Riyao Chen, Jinzhuo Jiang, Xiwen Luo

“…In an attempt to resolve the problems of the slow detection speed, low accuracy, and poor generalization ability of traditional detection models in the actual breeding environment, we propose a chicken behavior detection method called FCBD-DETR (Faster Chicken Behavior Detection Transformer). …”
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A Directional Wave Spectrum Inversion Algorithm with HF Surface Wave Radar Network by Fuqi Mo, Xiongbin Wu, Xiaoyan Li, Liang Yu, Heng Zhou

“…The results are shown to be in reasonable agreement at four typical locations in the core detection area. In addition, reasonable performance is also obtained under the condition of low SNRs, which further verifies the effectiveness of the proposed inversion algorithm.…”
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Fault Information Processing of Power Dispatching Communication System Combining MMSE Algorithm and LMS by Lianrong Pan, Xiao Yang, Yuan Fu, Yuyang Hu, Shangbin Yuan

“…Aiming at the defects of the existing power dispatching communication system, such as difficult to locate the fault information, low efficiency and poor accuracy, the research first introduces the minimum mean square error detection algorithm, and improves this algorithm. …”
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Application of a Channel Estimation Algorithm to Spectrum Sensing in a Cognitive Radio Context by Vincent Savaux, Moïse Djoko-Kouam, Yves Louët, Alexandre Skrzypczak

“…We theoretically show the convergence of the algorithm, and we derive its analytical detection and false alarm probabilities. …”
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Diagnostic algorithms in patients with chronic coronary syndromes — what does clinical practice show? by A. N. Sumin

“…The results obtained showed the effectiveness of novel diagnostic strategies in increasing the detection rate of obstructive CAD. However, clinical outcomes of any diagnostic algorithm are few and require further study, as well as their cost-effectiveness.…”
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Building Surface Defect Detection Based on Improved YOLOv8 by Xiaoxia Lin, Yingzhou Meng, Lin Sun, Xiaodong Yang, Chunwei Leng, Yan Li, Zhenyu Niu, Weihao Gong, Xinyue Xiao

“…To address these issues, an improved version of the You Only Look Once (YOLOv8) algorithm is proposed for building surface defect detection. …”
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Enabling Model-Based Design for Real-Time Spike Detection by Mattia Di Florio, Yannick Bornat, Marta Care, Vinicius Rosa Cota, Stefano Buccelli, Michela Chiappalone

“…MBD offers distinct advantages by streamlining the design workflow, from modelling to implementation, thus facilitating the development of intricate systems. A spike detection algorithm has been implemented on a commercially available system based on a Field-Programmable Gate Array (FPGA) that combines neural probe electronics with configurable integrated circuit. …”
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A Coevolutionary Algorithm Based on Constraints Decomposition for Constrained Multi-objective Optimization Problems by Guangpeng Li, Li Li, Guoyong Cai

“…The framework can take the advantage of the low complexity of single-constraint problems to help algorithm search the complete feasible regions. …”
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TATPat based explainable EEG model for neonatal seizure detection by Turker Tuncer, Sengul Dogan, Irem Tasci, Burak Tasci, Rena Hajiyeva

“…In this EFE model, there are four essential phases and these phases: (i) automaton and transformer-based feature extraction, (ii) feature selection deploying cumulative weight-based neighborhood component analysis (CWNCA), (iii) the Directed Lobish (DLob) and Causal Connectome Theory (CCT)-based explainable result generation and (iv) classification deploying t algorithm-based support vector machine (tSVM). In the first phase, we have used a channel transformer to get channel numbers and these values have been divided into three levels and these levels are named (1) high, (2) medium and (3) low. …”
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Investigation of AI Algorithms for Photometric Online Analysis in a Draft Tube Baffle Crystallizer by Laura Marsollek, Julius Lamprecht, Norbert Kockmann

“…The rapid advancement of AI algorithms presents new opportunities for sensing technologies based on image recognition, such as real-time crystallization monitoring. …”
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Advanced IoT-integrated parking systems with automated license plate recognition and payment management by Gulmini Pradhan, Manas Ranjan Prusty, Vipul Singh Negi, Suchismita Chinara

“…Testing under real-world conditions showed 95% accuracy in daylight, 90% in low light, and 93% for plates at 45-degree angles. …”
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Preset Conditional Generative Adversarial Network for Massive MIMO Detection by Yongzhi Yu, Shiqi Zhang, Jiadong Shang, Ping Wang

“…The detection performance of NR-PC-GAN is far superior to the other algorithms in low-SNR scenarios.…”
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