Development of a grape-harvesting robot using a multi-step detection method based on AI and a position-estimation algorithm by Weiguo Wang, Liangliang Yang, Noboru Noguchi

“…When only one or a small amount of target grape clusters exist in the image, the YOLOv7-Pose model is used to detect the key points of the grapes and output their coordinates to predict the correct cutting point for the robot's hand. …”
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A Novel Adaptive Fine-Tuning Algorithm for Multimodal Models: Self-Optimizing Classification and Selection of High-Quality Datasets in Remote Sensing by Yi Ren, Tianyi Zhang, Zhixiong Han, Weibin Li, Zhiyang Wang, Wenbo Ji, Chenhao Qin, Licheng Jiao

“…First, the vast dataset is projected into a semantic vector space, where the MiniBatchKMeans algorithm is used for automated clustering. This classification ensures that the data within each cluster exhibit high semantic similarity. …”
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An Innovative Indoor Localization Method for Agricultural Robots Based on the NLOS Base Station Identification and IBKA-BP Integration by Jingjing Yang, Lihong Wan, Junbing Qian, Zonglun Li, Zhijie Mao, Xueming Zhang, Junjie Lei

“…Finally, the improved black kite algorithm (IBKA) is enhanced with tent chaotic mapping, a lens imaging reverse learning strategy, and the golden sine strategy to optimize the weights and biases of the BP neural network, developing an RSSI-based ranging algorithm using the IBKA-BP neural network. …”
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Designing a new tomato leaf disease classification framework using ran-based adaptive fuzzy c-means with heuristic algorithm model by Kanti Rongali Divya, Rao Gottapu Sasibhushana, Aruna Singam

“…Meanwhile, the parameters of the AFCM algorithm complicate the cluster assignment in the presence of outliers or noise, thus resulting in reduced clustering performance. …”
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Determination of future gully erosion risk and its spatially quantitative interpretability of driving factors in regional scale using machine learning algorithms by Xin Liu, Dichen Wang, Mingming Guo, Xingyi Zhang, Zhuoxin Chen, Zhaokai Wan, Jielin Liu

“…Gullies were interpreted as line features based on Google Earth images with the resolution of 0.3–0.6 m and further confirmed by field investigation, so all gullies in study area is spatially accurate. …”
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Leveraging automated time-lapse microscopy coupled with deep learning to automate colony forming assay by Anusha Klett, Anusha Klett, Dennis Raith, Dennis Raith, Paula Silvestrini, Paula Silvestrini, Paula Silvestrini, Matías Stingl, Jonas Bermeitinger, Avani Sapre, Avani Sapre, Avani Sapre, Martin Condor, Roman Melachrinos, Mira Kusterer, Alexandra Brand, Guido Pisani, Guido Pisani, Evelyn Ullrich, Evelyn Ullrich, Evelyn Ullrich, Evelyn Ullrich, Marie Follo, Marie Follo, Jesús Duque-Afonso, Roland Mertelsmann, Roland Mertelsmann

“…Our automated platform utilizes a deep learning and multi-object tracking approach for colony counting. Brightfield images were used to train a YOLOv8 object detection network, achieving a mAP50 score of 86% for identifying single cells, clusters, and colonies, and 97% accuracy for Z-stack colony identification with a multi-object tracking algorithm. …”
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Measuring the Intracluster Light Fraction with Machine Learning by Louisa Canepa, Sarah Brough, Francois Lanusse, Mireia Montes, Nina Hatch

“…Upcoming large imaging surveys such as the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) are expected to vastly expand available samples of deep cluster images. …”
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Machine learning and microfluidic integration for oocyte quality prediction by Hassan Saffari, Davood Fathi, Peyman Palay, Hamid Gourabi, Rouhollah Fathi

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Transforming traffic accident investigations: a virtual-real-fusion framework for intelligent 3D traffic accident reconstruction by Yanzhan Chen, Qian Zhang, Fan Yu

“…This study proposes a novel virtual-real-fusion simulation framework that integrates traffic accident generation, unmanned aerial vehicle (UAV)-based image collection, and a 3D traffic accident reconstruction pipeline with advanced computer vision techniques and unsupervised 3D point cloud clustering algorithms. …”
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ICT-Net: A Framework for Multi-Domain Cross-View Geo-Localization with Multi-Source Remote Sensing Fusion by Min Wu, Sirui Xu, Ziwei Wang, Jin Dong, Gong Cheng, Xinlong Yu, Yang Liu

“…To facilitate practical deployment, we propose a deep embedding clustering algorithm optimized for rapid parsing of geo-localization information. …”
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Road Pothole Recognition and Size Measurement Based on the Fusion of Camera and LiDAR by Yongxiang Cai, Mingxing Deng, Xin Xu, Wei Wang, Xiaowei Xu

“…We then utilize roughness feature description and the Mean-shift clustering algorithm to extract precise sets of pothole points, which allows us to determine the depth, length, width, and relative coordinates of the potholes with respect to the vehicle. …”
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Mask R-CNN aided fruit surface temperature monitoring algorithm with edge compute enabled internet of things system for automated apple heat stress management by Basavaraj R. Amogi, Rakesh Ranjan, Lav R. Khot

“…Our prior study focused on development of internet of things (IoT) and edge-compute enabled crop physiology sensing system (CPSS) for apple sunburn monitoring. Edge compute algorithm on CPSS estimated sunburn susceptibility as fruit surface temperature (FST) through pixel-by-pixel multiplication of captured thermal infrared images with segmented fruits binary mask. …”
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Analysis of daytime land surface temperature in Iran based on the MODIS sensor output by Mahmoud Ahmadi, AbbasAli Dadashi Roudbari, Hamzeh Ahmadi

“…In this study, considering the significant precision of day-night-based physics algorithm, Wan et al. (2002) has used this method to study Daytime LST in Iran. …”
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Research on multi-sensor fusion detection and tracking technology for autonomous-rail rapid transit tram by PAN Wenbo, YUAN Xiwen, LIN Jun, XIE Guotao, LONG Teng, HUANG Wenyu

“…The approach was based on the point cloud range image, and the gradient and distance characteristics to solve the problem of clustering obstacles in changing scenes. …”
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An Infrared Small Moving Target Detection Method in Complex Scenes Based on Dual-Region Search by Huazhao Cao, Yuxin Hu, Ziming Wang, Jianwei Yang, Guangyao Zhou, Wenzhi Wang, Yuhan Liu

“…Infrared (IR) small target detection is a crucial component of infrared imaging systems and is vital for applications in surveillance, security, and early warning systems. …”
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Bridge Deformation Prediction Using KCC-LSTM With InSAR Time Series Data by Zechao Bai, Chang Shen, Yanping Wang, Yun Lin, Yang Li, Wenjie Shen

“…The approach initially combines two machine learning based clustering algorithms, K-Shape for better capturing shape features of time series and complete linkage hierarchical clustering combined with spatial geographic location captures the spatial characteristics of time series to derive clusters with unique spatiotemporal deformation behavior, improving clustering accuracy and spatiotemporal correlation. …”
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Rice Leaf Nutrient Deficiency Classification System Using CAR-Capsule Network by M. Amudha, K. Brindha

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Electric Power Consumption Forecasting Models and Spatio-Temporal Dynamic Analysis of China’s Mega-City Agglomerations Based on Low-Light Remote Sensing Imagery Incorporating Socia... by Cuiting Li, Dongmei Yan, Shuo Chen, Jun Yan, Wanrong Wu, Xiaowei Wang

“…Utilizing 2017–2021 NPP/VIIRS low-light remote sensing imagery to extract total nighttime light data, this study proposed an EPC prediction method based on the K-Means clustering algorithm combined with multiple indicators integrated with socio-economic factors. …”
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Incorporating environmental data to refine the classification and understanding of the mechanisms behind encroachment of a woody species in the Southern Great Plains (USA) by Justin Dawsey, Nancy E. McIntyre

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Unsupervised Feature Selection via a Dual-Graph Autoencoder with <inline-formula><math display="inline"><semantics><mrow><msub><mi mathvariant="bold-script">l</mi><mrow><mn mathvar... by Zhichao Song, Meiling Chen, Liang Xie, Xi Fang

“…Experiments on multiple benchmark datasets and [⁶⁸Ga]Ga-Pentixafor PET/CT glioma imaging data demonstrate that the proposed DGA significantly improves clustering performance and accurately identifies features associated with lesion regions. …”
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