FCB-YOLOv8s-Seg: A Malignant Weed Instance Segmentation Model for Targeted Spraying in Soybean Fields by Zishang Yang, Lele Wang, Chenxu Li, He Li

“…To address these challenges, this study proposes an improved weed instance segmentation model based on YOLOv8s-Seg, named FCB-YOLOv8s-Seg, for targeted spraying operations in soybean fields. …”
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Enhanced Feature Selection via Hierarchical Concept Modeling by Jarunee Saelee, Patsita Wetchapram, Apirat Wanichsombat, Arthit Intarasit, Jirapond Muangprathub, Laor Boongasame, Boonyarit Choopradit

“…The objectives of feature selection include simplifying modeling and making the results more understandable, improving data mining efficiency, and providing clean and understandable data preparation. …”
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Deep learning-based semantic segmentation with novel navigation line extraction for autonomous agricultural robots by Chijioke Leonard Nkwocha, Ning Wang

“…The results of the experiments showed that PSPNet achieved the highest mean intersection over union (mIoU) of 96.50%, followed by Deeplabv3+ (96.30%) and ENet (95.13%). While ENet showed more consistent performance across various lighting conditions, the novel algorithm demonstrated remarkable accuracy, reducing angle errors to an average of 1.1°, 1.6°, and 1.6° for ENet, Deeplabv3+, and PSPNet, respectively, compared to 4.6°, 4.9°, and 6.7° using the baseline method. …”
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Enhanced Detection of Intrusion Detection System in Cloud Networks Using Time-Aware and Deep Learning Techniques by Nima Terawi, Huthaifa I. Ashqar, Omar Darwish, Anas Alsobeh, Plamen Zahariev, Yahya Tashtoush

“…In contrast, Deep Neural Network (DNN) models showed significant improvements with optimization, with DNN combined with GS (DNN-GS) reaching 89% accuracy. …”
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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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Pengembangan Deep Learning untuk Sistem Deteksi Dini Komplikasi Kaki Diabetik Menggunakan Citra Termogram by Medycha Emhandyksa, Indah Soesanti, Rina Susilowati

“…In this study, four deep convolutional neural network models were designed with Occam's razor principle through hyperparameter settings on the algorithm structure aspect in the form of number of layers and optimization aspect in the form of optimizer type. …”
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A Multi-Mode Switching Energy Management Strategy Based on Travel Habits for Range-Extended Electric Vehicle by Zhenhai Gao, Guoqing Zhang, Hanwu Liu, Cheng Chang, Jingwen Dong, Rongrong He, Yu Cai

“…This strategy not only optimizes the energy allocation of vehicles under different road conditions, but also improves overall efficiency by reducing the frequency and time of APU system intervention. …”
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The Application of Artificial Intelligence in Medical Diagnostics: Implications for Sports Medicine by Michał Bolek, Dominika Musialska, Aleksandra Kędzia, Bartosz Jagieła, Monika Fidyk, Magda Minkiewicz, Maciej Dyda

“…Recent advancements allow AI systems to analyze physiological, biomechanical, and behavioral data, leading to improved injury prevention and performance optimization in athletes. …”
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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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A high performance approach to ensure image security during transmission by Adithya S Nair, Charvi Upreti, Advaith Arun, Renuka Devi S

“…The randomization is achieved through a Mersenne Twister algorithm. This project uses parallelization techniques to optimize computational performance and reduce the runtime. …”
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Revolutionize 3D-Chip Design With Open3DFlow, an Open-Source AI-Enhanced Solution by Yifei Zhu, Zhenxuan Luan, Dawei Feng, Weiwei Chen, Lei Ren, Zhangxi Tan

“…<italic>Open3DFlow</italic>&#x2019;s open-source nature allows seamless integration of custom AI optimization algorithms. As a showcase, we leverage large language models (LLMs) to help the bonding pad placement. …”
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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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Research on fine-grained classification of rare metal granite lithology based on deep learning by ZHAO Hengqian, WANG Pan, LIU Zhiguo, MIAO Qunfeng, LI Zhibin, TANG Guanglong, QI Yunfei, XIE Yu, WANG Mengmeng

“…In the future, the accuracy of fine-grained classification of rare metal granite lithology can be further improved by improving the quantity and quality of rock samples and optimizing the model algorithm.…”
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Deep learning-based technique for investigating the behavior of MEMS systems with multiwalled carbon nanotubes and electrically actuated microbeams by Muhammad Amir, Jamshaid Ul Rahman, Ali Hasan Ali, Ali Raza, Zaid Ameen Abduljabbar, Husam A. Neamah

“…Numerical simulations and graphical demonstrations are presented to verify the accuracy and efficiency of the algorithm. • The study develops a novel DNN-based model to solve non-linear systems in MEMS, particularly for oscillators with MWCNTs. • Deep learning optimizers are applied to improve the accuracy and efficiency of predicting MEMS behavior. • Numerical simulations confirm the effectiveness of the proposed methodology.…”
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rhBNN+ Comprehensive Detections and Analyses of the Human Body Temperatures and Sounds by the Same Smart Mask by Bingcan Liao, Pin Sun, Shuyi Chen, Rihong Huang, Junyu Yang, Guofeng Li, Chengzhi Lv, Nan Zhu, Shui Guan, Hailong Liu, Rong Liu, Ali Mansouri, Changkai Sun

“…The SVM achieved 84.3% accuracy for sound data classification, while the Lion algorithm−optimized SVM achieved an even higher accuracy of 93.6%. …”
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Forest cover and canopy health mapping in Australian subalpine landscape: supervised machine learning models for Sentinel-2 and Landsat images by Weerach Charerntantanakul, Marta Yebra, Hilary Rose Dawson, Adrienne Beth Nicotra, Saul Alan Cunningham, Matthew Theodore Brookhouse

“…In conclusion, constraining the region of interest and optimizing model configurations can improve forest cover mapping. …”
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Photovoltaic Power Forecasting with Weather Conditioned Attention Mechanism by Xuetao Jiang, Yuchun Gou, Meiyu Jiang, Lihui Luo, Qingguo Zhou

“…We propose a Multi-Stream Attention Fusion Network (MSAFN) which utilizes an algorithm to derive the optimal decomposition algorithm for different weather conditions. …”
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Enhancing proximal and remote sensing of soil organic carbon: A local modelling approach guided by spectral and spatial similarities by Qi Sun, Pu Shi

“…Different spectral similarity metrics, and weighted combinations of spectral and geographical similarity matrices were tested to optimize the selection of local training samples. As a result, the optimal modelling strategy, with partial least squares regression (PLSR) as the local fitting algorithm, consistently produced superior performances (R2: 0.66 to 0.82) than the conventional global modelling approach (R2: 0.59 to 0.77) for all three data types. …”
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DCE-YOLOv8: Lightweight and Accurate Object Detection for Drone Vision by Jinsu An, Dong Hee Lee, Muhamad Dwisnanto Putro, Byeong Woo Kim

“…When comparing the proposed method with the YOLOv8 small version using the VisDrone dataset, the mean Average Precision value improved by approximately 43%, increasing from 22.8mAP to 32.7mAP, while the number of parameters decreased by about 57%, from 11,166,560 to 4,822,382. …”
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A novel canopy water indicator for UAV imaging to monitor winter wheat water status by Meiyan Shu, Zhenghang Ge, Yang Li, Jibo Yue, Wei Guo, Yuanyuan Fu, Ping Dong, Hongbo Qiao, Xiaohe Gu

“…Considering variability across growth stages significantly improved the accuracy of water status quantification compared to assessments based on individual growth stages. …”
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