A New Approach to ORB Acceleration Using a Modern Low-Power Microcontroller by Jorge Aráez, Santiago Real, Alvaro Araujo

“…While it is faster than other feature detectors like SIFT (340 times faster) or SURF (15 times faster), it is one of the most computationally expensive algorithms in these types of systems. …”
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Research and application of flexible starting method for metro trains with permanent magnet motors based on PI control by LIU Zhicheng, CHEN Xijun, HE Ye, HU Hui

“…This solution focuses on optimizing cooperation among various subsystems during the starting process. …”
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Deadbeat-based control for MMC-HVDC power systems by Milovan Majstorović, Vaibhav Nougain, Leposava Ristić, Aleksandra Lekić

“…With the inherent advantages of lower computational burden and superior transient performance, AC current deadbeat controller is used for the modulation in OVL-MPC. To improve the robustness of the control method, the Moore–Penrose pseudo-inversion is applied to address control parameter mismatches, while the Smith predictor compensates for time delays. …”
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From Pixels to Diagnosis: Early Detection of Diabetic Retinopathy Using Optical Images and Deep Neural Networks by Amira J. Zaylaa, Sylva Kourtian

“…As future directions, it is necessary to develop a grading algorithm and to explore other strategies to further improve the automatic detection and diagnosis of DR and integrate it into digital slit lamp machines.…”
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Efficient vision transformers with edge enhancement for robust small target detection in drone-based remote sensing by Xuguang Zhu, Zhizhao Zhang

“…First, a Multi-Scale Edge Enhancement Fusion (MSEEF) module is designed, integrating adaptive pooling and edge-aware convolution to preserve target boundary details while enabling cross-scale feature interaction. Second, a Layered Attention Fusion (LAF) mechanism is developed, leveraging spatial depth-wise convolution and omnidirectional kernel feature fusion to improve hierarchical localization capability for densely occluded targets. …”
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Interval-Aware Scheduling of Surveillance Drones: Exact and Heuristic Approaches by Kaito Mori, Hiroki Nishikawa, Hiroyuki Tomiyama

“…In comparison to the Greedy method, the Multi-stage method achieved an average improvement of 37.8% in total flight time, while its algorithm runtime deteriorated by a maximum of 1.26 seconds. …”
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Research on the blockchain-based trusted ownership confirmation and value transfer system and its light weight of industrial data assets by WANG Dongchu, FU Yusun, YU Ya

“…The consensus protocol algorithm of the blockchain system was optimized based on the trustworthiness of nodes, reducing the probability of malicious attacks on nodes while improving the efficiency of system transaction consensus, achieving security and lightweight parallelism of the entire system. …”
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Deep learning-based detection and classification of acute lymphoblastic leukemia with explainable AI techniques by Debendra Muduli, Sourav Parija, Suhani Kumari, Asmaul Hassan, Harendra S. Jangwan, Abu Taha Zamani, Sk. Mohammed Gouse, Banshidhar Majhi, Nikhat Parveen

“…Additionally, we evaluated the performance of these models using different optimization techniques, including Adadelta, SGD, RMSprop, and Adam, to determine the most effective optimization strategy for improving classifica-tion accuracy. …”
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Automated analysis and textual summarization of time-varying references in advanced greenhouse climate control by Ramesh Arvind Naagarajan, Kiran Kumar Sathyanarayanan, Nadja Bauer, Stefan Streif, Stefan Streif

“…Potential reasons are the lack of transparency and the understandability of the control algorithms. This study introduces a language-based support system to improve the usability of advanced control strategies like MPC. …”
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Rolling Cargo Management Using a Deep Reinforcement Learning Approach by Rachid Oucheikh, Tuwe Löfström, Ernst Ahlberg, Lars Carlsson

“…In this paper, we apply state-of-the-art deep reinforcement learning algorithms to automate these operations in a complex and real environment. …”
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IMA-FLADRC-Based Electric-Driven High-Speed Maize Precision Seeding Control Strategy and System by Song Wang, Shujuan Yi, Bin Zhao, Yifei Li, Dongming Zhang, Tao Chen, Wensheng Sun

“…This study develops an electric-driven high-speed maize precision seeding control system, establishing kinematic models for the seeding and guiding motors relative to operating speed. An Improve Mayfly Algorithm-Fuzzy Linear Active Disturbance Rejection Control (IMA-FLADRC)-based control strategy is proposed, integrating a fuzzy algorithm to adaptively adjust the proportional coefficient of the Linear State Error Feedback (LSEF) and optimizing key parameters using an IMA, enhancing system adaptability and robustness. …”
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A longan-picking sequence planning method for UAV system based on multi-target tracking by Kaixuan Wu, Meiqi Zhang, Linlin Shi, Hengxu Chen, Yuju Mai, Mingda Luo, Hengyi Lin, Jun Li

“…A LonTsp planning algorithm is used for path planning, optimizing picking paths to reduce total picking time by 19.1% and lowering UAV energy consumption and time costs. …”
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Full-chain comprehensive assessment and multi-scenario simulation of geological disaster vulnerability based on the VSD framework: a case study of Yunnan province in China by Li Xu, Shucheng Tan, Runyang Li

“…In the economically oriented scenario, GDV predominantly stabilizes at moderate levels, while in the environment oriented scenario, GDV improves the fastest but subsequently shows a slight rebound. …”
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ST-YOLOv8: Small-Target Ship Detection in SAR Images Targeting Specific Marine Environments by Fei Gao, Yang Tian, Yongliang Wu, Yunxia Zhang

“…Furthermore, the ST-YOLOv8 model outperforms several state-of-the-art multi-scale ship detection algorithms on both datasets. In summary, the ST-YOLOv8 model, by integrating advanced neural network architectures and optimization techniques, significantly improves detection accuracy and reduces false detection rates. …”
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Anomaly Detection in Network Traffic Using Advanced Machine Learning Techniques by Stephanie Ness, Vishwanath Eswarakrishnan, Harish Sridharan, Varun Shinde, Naga Venkata Prasad Janapareddy, Vineet Dhanawat

“…By comparing different algorithms, this research contributes to advancing the application of machine learning in network security, offering guidance on model selection and optimization for improved detection of cyber threats.…”
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Trading off Iodine and Radiation Dose in Coronary Computed Tomography by Guillaume Fahrni, Thomas Saliba, Damien Racine, Marianna Gulizia, Georgios Tzimas, Chiara Pozzessere, David C. Rotzinger

“…This review explores the balance between radiation and CM volumes, emphasizing patient-specific protocol optimization to improve diagnostic accuracy while minimizing risks. …”
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Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques by Negin Ashrafi, Armin Abdollahi, Kamiar Alaei, Maryam Pishgar

“…XGBoost emerged as the top performing algorithm, achieving an AUC of 0.94 and an accuracy of 0.875 on the test set, marking substantial improvements over previously reported best results. …”
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A Hierarchical Control Framework for Coordinating CAV-Dedicated Lane Allocation and Signal Timing at Isolated Intersections in Mixed Traffic Environments by Feng Chen, Cunbao Zhang, Yu Cao

“…The framework employs two collaborative agents based on the dueling double deep Q-network (D3QN) algorithm. The upper-level agent recommends optimal CAV-DLs configurations based on long-term traffic flow patterns, while the lower-level agent focuses on real-time signal control by adjusting signal parameters and green time allocations in response to current traffic demand. …”
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UAV Path Planning for Precision Multi-Target Localization by Mahsa Mohammadi, Michael W. Shafer

“…Recent advancements in Uncrewed Aerial Vehicles (UAVs) have expanded the potential for improving this process. However, a key challenge lies in the optimal choice of waypoints for UAVs to localize animals with high precision. …”
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Enhancing Latent Defect Detection in Built-In Spindle Assembly Lines Through Vibration Data Analysis by Kuo-Hao Li, Chao-Nan Wang, Yao-Chi Tang

“…The integration of these advanced algorithms accurately identified defects and categorized them, thus optimizing manufacturing processes. …”
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