Adaptive Q-Learning Grey Wolf Optimizer for UAV Path Planning by Golam Moktader Nayeem, Mingyu Fan, Golam Moktader Daiyan

“…Path planning is crucial for safely and efficiently navigating unmanned aerial vehicles (UAVs) toward operational goals. Often, this is a complex, multi-constraint, and non-linear optimization problem, and metaheuristic algorithms are frequently used to solve it. …”
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Optimizing UAV performance with IoT and fuzzy linear fractional transportation models by Samaher Al-Janabi, Nawras G. Seyhood

“…Unmanned aerial vehicles (UAVs) have become indispensable in replacing human pilots for high-risk, high-intensity operations, including search-and-rescue missions, infrastructure inspection, and environmental monitoring. …”
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Trajectory Optimization for UAV-Aided IoT Secure Communication Against Multiple Eavesdroppers by Lingfeng Shen, Jiangtao Nie, Ming Li, Guanghui Wang, Qiankun Zhang, Xin He

“…This study concentrates on physical layer security (PLS) in UAV-aided Internet of Things (IoT) networks and proposes an innovative approach to enhance security by optimizing the trajectory of unmanned aerial vehicles (UAVs). …”
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Control Allocation Strategy Based on Min–Max Optimization and Simple Neural Network by Kaixin Li, Mei Liu, Xinliang Li, Xiaobin Yu, Kun Liu

“…Additionally, an offline-trained neural network is employed to replace the online optimization process, enabling the complete controller to operate on the flight control board without relying on an onboard computer. …”
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Control-Oriented Real-Time Trajectory Planning for Heterogeneous UAV Formations by Weichen Qian, Wenjun Yi, Shusen Yuan, Jun Guan

“…By pre-training trajectory prediction networks for various types of UAVs, the traditional physics-based models are replaced for flight trajectory prediction. …”
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Optimization of Table Tennis Swing Action Supported by the Temporal Convolutional Network Algorithm in Deep Learning by Shaoxuan Sun, Hongyu Zheng, Zhixin Lin

“…This research outcome offers new insights into the application of UAVs in sports analysis and lays the groundwork for optimizing models and feature extraction techniques in broader sports application scenarios.…”
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A Bionic Social Learning Strategy Pigeon-Inspired Optimization for Multi-Unmanned Aerial Vehicle Cooperative Path Planning by Yankai Shen, Xinan Liu, Xiao Ma, Hong Du, Long Xin

“…This paper proposes a bionic social learning strategy pigeon-inspired optimization (BSLSPIO) algorithm to tackle cooperative path planning for multiple unmanned aerial vehicles (UAVs) with cooperative detection. …”
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Application of Reinforcement Learning in Controlling Quadrotor UAV Flight Actions by Shang-En Shen, Yi-Cheng Huang

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Automatic collaborative water surface coverage and cleaning strategy of UAV and USVs by Tianping Deng, Xiaohui Xu, Zeyan Ding, Xiao Xiao, Ming Zhu, Kai Peng

“…In addition, Unmanned Surface Vessels (USVs) can provide battery replacement and pick up garbage. In this paper, we innovatively establish a system framework for the collaboration between UAV and USVs, and develop an automatic water cleaning strategy. …”
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Detecting Planting Holes Using Improved YOLO-PH Algorithm with UAV Images by Kaiyuan Long, Shibo Li, Jiangping Long, Hui Lin, Yang Yin

“…The identification and detection of planting holes, combined with UAV technology, provides an effective solution to the challenges posed by manual counting, high labor costs, and low efficiency in large-scale planting operations. …”
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AGW-YOLO-Based UAV Remote Sensing Approach for Monitoring Levee Cracks by HU Weibo, ZHOU Shaoliang, ZHAO Erfeng, ZHAO Xueqiang

“…Finally, to address the multi-scale variation of cracks, the original loss function was replaced with WIoUv3. This loss function incorporates an outlier degree evaluation and a dynamic non-monotonic focusing mechanism, which adaptively adjusts the optimization intensity of anchor boxes with varying qualities. …”
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Research on Buckwheat Weed Recognition in Multispectral UAV Images Based on MSU-Net by Jinlong Wu, Xin Wu, Ronghui Miao

“…Targeting low detection efficiency in complex agricultural environments and inability of multispectral input in weed recognition of minor grain based on unmanned aerial vehicles (UAVs), a semantic segmentation model for buckwheat weeds based on MSU-Net (multispectral U-shaped network) was proposed to explore the influence of different band optimizations on recognition accuracy. …”
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SDFA-Net: Synergistic Dynamic Fusion Architecture With Deformable Attention for UAV Small Target Detection by Yunsong Qi, Hengwei Cao

“…Through cross-domain validation of the ALU and HIT-UAV datasets, the ablation experiments and comparative analysis fully validated the effectiveness of the algorithmic improvement, and its detection accuracy and robustness were significantly improved over the baseline model. …”
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LMSOE-Net: lightweight multi-scale small object enhancement network for UAV aerial images by Zhixing Ma, Peidong Luo, Xiaole Shen

“…Abstract Detecting objects of varying scales, especially small ones, in Unmanned Aerial Vehicle (UAV) aerial images across diverse scenarios and viewpoints using onboard edge devices is a major challenge in computer vision. …”
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Application of Quantum Key Distribution to Enhance Data Security in Agrotechnical Monitoring Systems Using UAVs by Makhabbat Bakyt, Luigi La Spada, Nida Zeeshan, Khuralay Moldamurat, Sabyrzhan Atanov

“…Ensuring secure data transmission in agrotechnical monitoring systems using unmanned aerial vehicles (UAVs) is critical due to increasing cyber threats, particularly with the advent of quantum computing. …”
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Small Target Detection Algorithm for UAV Aerial Images Based on Improved YOLOv7-tiny by ZHANG Guanghua, LI Congfa, LI Gangying, LU Weidang

“…This study proposes a small target detection algorithm for UAV aerial images using a ConvMixer detection head based on the improved YOLOv7-tiny to address the problems of missed detection and false detection caused by significant variations in target scale, densely distributed small-sized targets and complex backgrounds in UAV aerial images.MethodsFirst, the activation function LeakyReLU is replaced with SiLU to compensate for the limited nonlinear expression of LeakyReLU and to enhance convergence speed and model generalization during training. …”
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Toward Efficient UAV-Based Small Object Detection: A Lightweight Network with Enhanced Feature Fusion by Xingyu Di, Kangning Cui, Rui-Feng Wang

“…Then, DyHead is used to replace the original detector head, and the discrimination ability of small targets in complex background is enhanced by adaptive weight allocation and cross-scale feature optimization fusion. …”
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Enhanced fire hazard detection in solar power plants: an integrated UAV, AI, and SCADA-based approach by Andrii Lysyi, Anatoliy Sachenko, Pavlo Radiuk, Mykola Lysyi, Oleksandr Melnychenko, Oleksii Ishchuk, Oleg Savenko

“…This capability allows the system to reliably differentiate between true emergencies requiring immediate module replacement and less critical issues, such as soiling that merely necessitates cleaning. …”
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YOLO-DroneMS: Multi-Scale Object Detection Network for Unmanned Aerial Vehicle (UAV) Images by Xueqiang Zhao, Yangbo Chen

“…In recent years, research on Unmanned Aerial Vehicles (UAVs) has developed rapidly. Compared to traditional remote-sensing images, UAV images exhibit complex backgrounds, high resolution, and large differences in object scales. …”
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A band selection method for consumer-grade camera modification for UAV-based rapeseed growth monitoring by Chufeng Wang, Jian Zhang, Hao Wu, Bin Liu, Botao Wang, Yunhao You, Zuojun Tan, Jing Xie, Liangzhi You, Junqiang Zhang, Ping Wen

“…To this end, the normalized difference spectral index (NDSI) and the ratio spectral index (RSI) formulations were used to calculate the spectral indices (SIs) from all possible combinations of any two center wavelengths in UAV hyperspectral data. The contour maps of the coefficient of determination (R2) between the SIs and ground-measured rapeseed LAI were then computed to automatically generate the broadband combinations with optimized center wavelengths and effective bandwidths for selecting filters on camera modification. …”
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