Focus on Disaster Risk Reduction by ResNet-CDMV Model After Natural Disasters by Zhaojia Tang, Yu Han

“…We proposed a multi-model cluster decision method to extract the secondary disaster factors’ visual features, and we created a ResNet-CDMV image classification algorithm with higher accuracy recognition performance than the traditional single model. …”
Get full text

Time series classification through visual pattern recognition by Agnieszka Jastrzebska

“…Furthermore, the proposed conversion of raw time series into images that are subjected to feature extraction opens the possibility to apply standard clustering algorithms.…”
Get full text

Transmission Line Anomaly Detection and Real-Time Monitoring System Combining Edge Computing and EfficientDet by Menghao Lin, Yang Ding, Tianle Wang, Yang Liu, Zewei Li

“…This paper develops a transmission line anomaly detection and real-time monitoring system combining edge computing and improved Efficient Det based on the characteristics of foreign object images. Firstly, by collecting abnormal images of transmission channels, the Retinex algorithm is used to enhance the input images. …”
Get full text

MRI-guided clustering of patients with mild dementia due to Alzheimer's disease using self-organizing maps by Kellen K. Petersen, Bhargav T. Nallapu, Richard B. Lipton, Ellen Grober, Ali Ezzati

Get full text

An enhanced method of CNNs by incorporating the clustering-guided block for concrete crack recognition by Hui Li, Chenyu Liu, Ning Zhang, Wei Shi

“…The innovative CG block operates by categorizing extracted image features into K groups, merging these features, and then simultaneously feeding the augmented features and original image into the CNN for precise crack image segmentation. …”
Get full text

A Novel THz Differential Spectral Clustering Recognition Method Based on t-SNE by Tie-Jun Li, Chih-Cheng Chen, Jian-jun Liu, Gui-fang Shao, Christopher Chun Ki Chan

“…Comparative experiments indicate that our model can judge the existence of sample defect features or not through spectrum clustering, as a predetection process for image analysis.…”
Get full text

Enhanced Landslide Visualization and Trace Identification Using LiDAR-Derived DEM by Jie Lv, Chengzhuo Lu, Minjun Ye, Yuting Long, Wenbing Li, Minglong Yang

“…Moreover, based on the enhanced display images, the fractal model and the Mean-Shift algorithm are applied for denoising to extract landslide traces. …”
Get full text

Automated pavement marking integrity assessment using a UAV platform – a test case of public parking by Payam Rahnamayiezekavat, Di Wang, Jian Chai, Sungkon Moon, Maria Rashidi, Xiangyu Wang

“…Given intensity differences between pixels of paintings and asphalt backgrounds, the pixels belonging to painting regions are classified using the K-mean clustering algorithm. After detecting all parking lines from images, the Otsu method was employed to determine the threshold of 0.9 as the quantitative indicator of painting quality. …”
Get full text

Development of a technique to identify μm-sized organic matter in asteroidal material: An approach using machine learning by Rahul Kumar, Katsura Kobayashi, Christian Potiszil, Tak Kunihiro

“…We found that identifying OM is more accurate by classification with machine learning than by clustering. On the approach of classification with machine learning, five algorithms were tested. …”
Get full text

MCC: Multi-Cluster Contrastive Semi-Supervised Segmentation Framework for Echocardiogram Videos by Yu-Jen Chen, Shr-Shiun Lin, Yiyu Shi, Tsung-Yi Ho, Xiaowei Xu

“…Leveraging contrastive loss to enhance foreground feature extraction, our method incorporates multi-cluster contrastive loss to utilize multiple annotated ground-truths per batch and an anchor frame selection algorithm to improve segmentation performance. …”
Get full text

Using Neural Networks to Automate the Identification of Brightest Cluster Galaxies in Large Surveys by Patrick Janulewicz, Tracy M. A. Webb, Laurence Perreault-Levasseur

“…Brightest cluster galaxies (BCGs) lie deep within the largest gravitationally bound structures in existence. …”
Get full text

kMetha-Mamba: K-means clustering mamba for methane plumes segmentation by Yuquan Liu, Hailiang Shi, Ke Cao, Shichao Wu, Hanhan Ye, Xianhua Wang, Erchang Sun, Yunfei Han, Wei Xiong

“…However, traditional k-means clustering algorithms are susceptible to the influence of outliers. …”
Get full text

Privacy-preserved data hiding using compressive sensing and fuzzy C-means clustering by Ming Li, Lanlan Wang, Haiju Fan

“…The original image is preprocessed first to generate multiple highly correlated classes with fuzzy C-means clustering algorithm. …”
Get full text

An intelligent algorithm for identifying dropped blocks in wellbores by Qian Wang, Zixuan Yang, Chenxi Ye, Wenbao Zhai, Xiao Feng

“…The raw data obtained were preprocessed using methods such as format conversion, down sampling, coordinate transformation, statistical filtering, and clustering. Feature extraction algorithms, including the principal component analysis bounding box method, triangular meshing method, triaxial projection method, local curvature method, and model segmentation projection method, were employed, which resulted in the extraction of 32 feature parameters from the point cloud data. …”
Get full text

Advanced clustering and transfer learning based approach for rice leaf disease segmentation and classification by Samia Nawaz Yousafzai, Fahd N. Al-Wesabi, Hadeel Alsolai, Shouki A. Ebad, Inzamam Mashood Nasir, Emad Fadhal, Adel Thaljaoui

“…Diseased regions are then segmented through the developed gravity weighted kernelised density clustering algorithm. In terms of feature extraction, EfficientNetB0 is fine-tuned by subtracting the last fully connected layers, and the classification is conducted with the new fully connected layers. …”
Get full text

ONLINE FUZZY CLUSTERING OF HIGH DIMENSION DATA STREAMS BASED ON NEURAL NETWORK ENSEMBLES by Yevgeniy Bodyanskiy, Iryna Perova, Polina Zhernova

“…In the event the reduction-compression procedure cannot be used due to the probability of losing the physical meaning of the original space, a new clustering criterion was introduced; this criterion contains both a well-known polynomial fuzzifier and the weighment of individual components of the deviations of presented images from cluster centroids. …”
Get full text

Genotyping Identification of Maize Based on Three-Dimensional Structural Phenotyping and Gaussian Fuzzy Clustering by Bo Xu, Chunjiang Zhao, Guijun Yang, Yuan Zhang, Changbin Liu, Haikuan Feng, Xiaodong Yang, Hao Yang

“…The research results showed that the Gaussian Fuzzy Clustering algorithm was the optimal choice for clustering maize genotypes. …”
Get full text

A System for the Real-Time Detection of the U-Shaped Steel Bar Straightness on a Production Line by Yen-Jen Chen, Yu-Hsiu Yeh, Jen-Fu Yang

Get full text

Research on Recognition of Green Sichuan Pepper Clusters and Cutting-Point Localization in Complex Environments by Qi Niu, Wenjun Ma, Rongxiang Diao, Wei Yu, Chunlei Wang, Hui Li, Lihong Wang, Chengsong Li, Pei Wang

“…This study compared the performance of multiple You Only Look Once (YOLO) algorithms for recognition and proposed a cluster segmentation method based on K-means++ and a cutting-point localization strategy using geometry-based iterative optimization. …”
Get full text

Mapping the Impact of Spontaneous Streetscape Features on Social Sensing in the Old City of Quanzhou, China: Based on Multisource Data and Machine Learning by Keran Li, Yan Lin

“…This paper combined the mobile collection of street view images (SVIs) and a machine learning algorithm to calculate eight types of spontaneous streetscape elements and integrated two online platforms (Dianping and Sina Weibo) to map the distribution of economic vitality and social media perception, respectively. …”
Get full text