Plant recognition of maize seedling stage in UAV remote sensing images based on H-RT-DETR by Yunlong Wu, Shouqi Yuan, Lingdi Tang

“…In order to quickly and accurately identify and count maize seedlings in a complex field environment, this study proposes an end-to-end maize seedling plant detection model H-RT-DETR (Hierarchical-Real-Time DEtection TRansformer) based on hierarchical feature extraction and RT-DETR (Real-Time DEtection TRansformer). …”
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Cellulosic-based microneedles for sensing heavy metals in fish samples by Houman Kholafazad, Mahdiyeh Pazhuhi, Mohammad Hasanzadeh, Nicolas H. Voelcker, Nasrin Shadju, Azadeh Nilghaz

“…The MNs exhibit low reagent and sample volume requirements along with flexibility and ease of penetration into samples, and filtration capabilities that allow efficient detection with minimal interference. The structure of MNs was investigated by field emission scanning electron microscopy (FE-SEM), revealing a conical shape with an average height of ∼750 µm and a diameter of ∼500 µm. …”
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PlantHealthNet: Transformer-Enhanced Hybrid Models for Disease Diagnosis and Severity Estimation in Agriculture by Abid Iqbal

“…The suggested system improves precision agriculture by making disease detection and management reliable, scalable, and efficient. …”
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Defense scheme for the world state based attack in Ethereum by Zhen GAO, Dongbin ZHANG, Xiao TIAN

“…Ethereum is taken as the representative platform of the second generation of blockchain system.Ethereum can support development of different distributed applications by running smart contracts.Local database is used to store the account state (named world state) for efficient validation of transactions, and the state root is stored in the block header to guarantee the integrity of the state.However, some researches revealed that the local database could be easily tempered with, and attackers can issue illegal transactions based on the modified account state to obtain illegitimate benefits.This world-state based security problem was introduced, and the preconditions for attack were analyzed.Compared with the two common security threats under the PoW (proof of work) consensus, it was found that when the attacker controls the same mining computing power, the world-state based attack brought higher risk, and the success rate approached 100%.In order to deal with this threat, a practical scheme for attack detection and defense was proposed accordingly.The secondary verification and data recovery process were added to the Ethereum source code.The feasibility and complexity of the proposed scheme was evaluated with single-machine multi-threading experiments.The proposed scheme improves Ethereum’s tolerance to malicious tampering of account state, and is applicable to other blockchain platforms applying local database for transaction validation, such as Hyperledger Fabric.In addition, the time and computational overhead brought by the proposed scheme are not prominent, so it has good applicability and induces acceptable impact on the performance of original system.…”
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Determination of 15 Rare Earth Elements in Phosphate Ores by Inductively Coupled Plasma-Mass Spectrometry with Atmospheric Pressure Closed Microwave Digestion by Nan ZHANG, Zhikang ZHENG, Jiasong WANG, Jiangping ZENG

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Optimizing Fire Scene Analysis: Hybrid Convolutional Neural Network Model Leveraging Multiscale Feature and Attention Mechanisms by Shakhnoza Muksimova, Sabina Umirzakova, Mirjamol Abdullaev, Young-Im Cho

“…The proposed model integrates advanced convolutional neural networks with multiscale feature extraction, attention mechanisms, and ensemble learning to achieve superior performance in real-time fire detection. By leveraging the strengths of pre-trained networks such as ResNet50, VGG16, and EfficientNet-B3, the model captures detailed features at multiple scales, ensuring robust detection capabilities. …”
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Uncertainty CNNs: A path to enhanced medical image classification performance by Vasileios E. Papageorgiou, Georgios Petmezas, Pantelis Dogoulis, Maxime Cordy, Nicos Maglaveras

“…In this paper, we introduce a low-complexity uncertainty-based CNN architecture for medical image classification, particularly focused on tumor and heart failure (HF) detection. …”
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Multi-mode selective OFDM index modulation transmission scheme by GUO Yi, ZHU Yuchen, WANG Yiqing, LIU Gang, FU Shaozhong

“…Meanwhile, due to the subcarrier activation mode of the proposed scheme matching binary digits, the system could adopt a low complexity log likelihood ratio detection algorithm and maintained good bit error rate performance. …”
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An Automated Image Segmentation, Annotation, and Training Framework of Plant Leaves by Joining the SAM and the YOLOv8 Models by Lumiao Zhao, Kubwimana Olivier, Liping Chen

“…Recognizing plant leaves in complex agricultural scenes is challenging due to high manual annotation costs and real-time detection demands. …”
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Temporal Convolutional Network Approach to Secure Open Charge Point Protocol (OCPP) in Electric Vehicle Charging by Ikram Benfarhat, Vik Tor Goh, Chun Lim Siow, Muhammad Sheraz, Teong Chee Chuah

“…However, these models often struggle to effectively handle the temporal dependencies, complexity, and scalability required for real-time threat detection. …”
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End-of-Line Quality Control Based on Mel-Frequency Spectrogram Analysis and Deep Learning by Jernej Mlinarič, Boštjan Pregelj, Gregor Dolanc

“…These methods struggle to detect complex or subtle patterns associated with early-stage faults. …”
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Drainage Pipeline Multi-Defect Segmentation Assisted by Multiple Attention for Sonar Images by Qilin Jin, Qingbang Han, Jianhua Qian, Liujia Sun, Kao Ge, Jiayu Xia

“…Drainage pipeline construction projects are vulnerable to a range of defects, such as branch concealed joints, variable diameter, two pipe mouth significances, foreign object insertion, pipeline rupture, and pipeline end disconnection, generated during long-term service in a complex environment. This paper proposes two enhancements to multiple attention learning to detect and segment multiple defects. …”
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Technology of automated video observation of a drogue-sensor basket in the problem of autonomous aerial refueling by A. V. Gaidenkov, M. I. Kanevskiy, A. S. Ostrovskiy, O. I. Ganyak, N. Yu. Chizhov

“…A modeling complex for a synthetic vision system operation is presented. …”
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Radar target detector based on banded sample autocovariance matrices by Chang Qu, Xiaoying Wang, Jing Chen, Junping Yin, Jiang Hu, Zhigen Gao

“…Abstract Detecting weak radar targets in complex cluttered environments remains a significant challenge, particularly when attempting to effectively detect low signal-to-clutter ratio (SCR) targets while maintaining a constant false alarm rate (CFAR). …”
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Optimized AI and IoT-Driven Framework for Intelligent Water Resource Management by Mahmoud Badee Rokaya Mahmoud, Dalia Ismaeil Ibrahim Hemdan, Samah Hazzaa Alajmani, Raneem Yousif Alyami, Ghada Elmarhomy, Hassan Hashim, El-Sayed Atlam

“…However, water leak detection and irrigation scheduling traditional AI models are often computationally intensive and require complex hyperparameter tuning, making them less scalable. …”
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Three-dimensional optical path extended gourd-type photoacoustic cell for highly sensitive trace acetylene sensing by Chuanwen Qian, Wenjun Ni, Chunyong Yang, Zhongke Zhao, Likang Zhang, Sixiang Ran, Chenyu Wang, Ping Lu, Perry Ping Shum

“…GTPAC achieves an exceptionally high sensitivity of up to 3.36 μV/ppm using a distributed feedback butterfly laser with central wavelength of 1532 nm (±1.5 nm) to detect acetylene gas. When the integration time is extended to 100 s, the minimum detection limit is as low as 0.59 ppb. …”
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The influence of the molecular weight of hyaluronic acid on the mangiferin release kinetics from the polymer matrix by P. P. Snetkov, R. O. Shaikenov, V. I. Klimshina, Yu. E. Generalova, S. N. Morozkina

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Laser-induced Breakdown Spectroscopy Based on Pre-classification Strategy for Quantitative Analysis of Rock Samples by Weiheng KONG, Lingwei ZENG, Yu RAO, Sha CHEN, Xu WANG, Yanting YANG, Yixiang DUAN, Qingwen FAN

“…However, the existence of matrix effects and spectral fluctuations always affects the accuracy of LIBS quantitative analysis, and poor reproducibility and high detection limits also need to be solved.OBJECTIVESTo improve the accuracy of quantitative analysis of complex matrix samples.METHODSA multi-layer classification model based on k-nearest neighbors (kNN) and support vector machine (SVM) algorithms was constructed to identify the rock type of samples. …”
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Optimization of Flight Scheduling in Urban Air Mobility Considering Spatiotemporal Uncertainties by Lingzhong Meng, Minggong Wu, Xiangxi Wen, Zhichong Zhou, Qingguo Tian

“…The vigorous development of urban air mobility (UAM) is reshaping the urban travel landscape, but it also poses severe challenges to the safe and efficient operation of dense and complex airspace. …”
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Precise Spatial Prediction of Rice Seedlings From Large-Scale Airborne Remote Sensing Data Using Optimized Li-YOLOv9 by Jayakrishnan Anandakrishnan, Arun Kumar Sangaiah, Hendri Darmawan, Nguyen Khanh Son, Yi-Bing Lin, Mohammed J. F. Alenazi

“…However, the limited computational capabilities of UAVs make it challenging to deploy complex object detection models onboard. This article proposes Li-YOLOv9, an efficient, lightweight, and precise object detection model for detection of rice seedlings from large-scale UAV remote sensing data. …”
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