Assessing climate risks from satellite imagery with machine learning: A case study of flood risks in Jakarta by Jeasurk Yang, Donghyun Ahn, Junbeom Bahk, Sungwon Park, Nurrokhmah Rizqihandari, Meeyoung Cha

“…In doing so, we adopt a clustering-based supervised algorithm to sort satellite images to produce the climate risk scores at a grid-level. …”
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Fuzzy Logic Concepts, Developments and Implementation by Reza Saatchi

“…Fuzzy logic has been successfully combined with other artificial intelligence techniques such as artificial neural networks, deep learning, robotics, and genetic algorithms, creating powerful tools for complex problem-solving applications. …”
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Real-time Detection and Tracking for Operating Vehicles in Complex Mining Environments by KANG Gaoqiang, LIN Jun, LIU Shiwang, YUE Wei, XIONG Qunfang, TONG Hao

“…Aiming at the problems of poor detection effect and low tracking stability of multi-type vehicles in complex mining environment due to the similarity of operating vehicles and background images, this paper proposes a multi-category and multi-target real-time detection and tracking algorithm for operating vehicles in complex mining environments. …”
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Particle Swarm Optimization on Parallel Computers for Improving the Performance of a Gait Recognition System by Shahla A. Abdulqader, Hasmek A. Krekorian

“…This study presents the use of parallel computing approaches (PCA) to implement PSO for a GR system (GRS) to decrease processing while maintaining reconstructed image quality. These approaches are: Codistributor and parallel cluster. …”
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Advancing multi-categorization and segmentation in brain tumors using novel efficient deep learning approaches by Nadenlla RajamohanReddy, G. Muneeswari

“…Results Finally, a novel LWIFCM_CSA approach is introduced, which is the ensemble of Local-information weighted intuitionistic Fuzzy C-means clustering algorithm (LWIFCM) and Chameleon Swarm Algorithm (CSA). …”
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Design of an efficient multi-objective recognition approach for 8-ball billiards vision system by Jiaying Gao, Qiuyang He, Hong Gao, Zhixin Zhan, Zhe Wu

“…In the experiment, the proposed approach has been proved to complete the detection with an accuracy of 99.4% in 0.65s in average, and the performance is better than the traditional Circular Hough Transform (CHT) algorithm and the K-means cluster method. In addition, the Convolution Neural Network (CNN) method is adopted for pattern recognition of each target ball being segmented, i.e. identification of a solid ball or a striped ball. …”
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An automated hybrid deep learning framework for paddy leaf disease identification and classification by Chatla Subbarayudu, Mohan Kubendiran

“…Images of paddy leaves were obtained from the paddy doctor dataset hosted on Kaggle. …”
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Study of the Characteristics of a Co-Seismic Displacement Field Based on High-Resolution Stereo Imagery: A Case Study of the 2024 MS7.1 Wushi Earthquake, Xinjiang by Chenyu Ma, Zhanyu Wei, Li Qian, Tao Li, Chenglong Li, Xi Xi, Yating Deng, Shuang Geng

“…Subsequently, we applied the Iterative Closest Point (ICP) algorithm to perform differencing analysis on these datasets. …”
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Application of machine learning in corrosion inhibition study by Thankappan Sasilatha, Susai Rajendran, Senthil Kumaran Selvaraj, Časlav Lacnjevac, Rajendran Joseph Rathish

“…Machine Learning technologies are increasingly being used in medical imaging. To detect tumours and other malignant growths in the human body. …”
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The Hybrid Market Segmentation of Electric Vehicles in Ukraine Using Data Science Methods by Andrusyk Yevhenii V., Guryanova Lidiya S.

“…To solve the tasks set, a comprehensive approach was applied, incorporating Data Science methods: descriptive statistics, data collection through Data Scraping techniques, natural language processing (NLP) for thematic modeling and sentiment analysis of the reviews, as well as cluster analysis using the k-means algorithm. In the first stage, the analysis of structured data allowed for the identification of key market trends and revealed a paradoxical polarization of demand: consumers predominantly choose either budget models with a small range or premium cars with maximum range. …”
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Historical Manuscripts Analysis: A Deep Learning System for Writer Identification Using Intelligent Feature Selection with Vision Transformers by Merouane Boudraa, Akram Bennour, Mouaaz Nahas, Rashiq Rafiq Marie, Mohammed Al-Sarem

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Increasing Neural-Based Pedestrian Detectors’ Robustness to Adversarial Patch Attacks Using Anomaly Localization by Olga Ilina, Maxim Tereshonok, Vadim Ziyadinov

“…In this manuscript, we propose a method which helps to increase the robustness of neural network systems to the input adversarial images. The proposed method consists of a Deep Convolutional Neural Network to reconstruct a benign image from the adversarial one; a Calculating Maximum Error block to highlight the mismatches between input and reconstructed images; a Localizing Anomalous Fragments block to extract the anomalous regions using the Isolation Forest algorithm from histograms of images’ fragments; and a Clustering and Processing block to group and evaluate the extracted anomalous regions. …”
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To accurately predict lymph node metastasis in patients with mass-forming intrahepatic cholangiocarcinoma by using CT radiomics features of tumor habitat subregions by Pengyu Chen, Zhenwei Yang, Peigang Ning, Hao Yuan, Zuochao Qi, Qingshan Li, Bo Meng, Xianzhou Zhang, Haibo Yu

“…Using information from the arterial and venous phases of multisequence CT images, tumor habitat subregions were delineated through the K-means clustering algorithm. …”
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Integrative radiomics of intra- and peri-tumoral features for enhanced risk prediction in thymic tumors: a multimodal analysis of tumor microenvironment contributions by Liang zhu, Jiamin Li, Xuefeng Wang, Yan He, Siyuan Li, Shuyan He, Biao Deng

“…Subsequently, hierarchical clustering and the LASSO algorithm were applied to identify the most predictive features. …”
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Computed tomography-based radiomics predicts prognostic and treatment-related levels of immune infiltration in the immune microenvironment of clear cell renal cell carcinoma by Shiyan Song, Wenfei Ge, Xiaochen Qi, Xiangyu Che, Qifei Wang, Guangzhen Wu

“…The Single Sample Gene Set Enrichment Analysis (ssGSEA) algorithm was used to obtain the immune cell infiltration results as well as the cluster analysis results. ssGSEA-based analysis was used to obtain the immune cell infiltration levels, and the Boruta algorithm was further used to downscale the obtained positive/negative gene sets to obtain the immune infiltration level groupings. …”
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Sparse Representation of Deformable 3D Organs with Spherical Harmonics and Structured Dictionary by Dan Wang, Ahmed H. Tewfik, Yingchun Zhang, Yunhe Shen

“…This paper proposed a novel algorithm to sparsely represent a deformable surface (SRDS) with low dimensionality based on spherical harmonic decomposition (SHD) and orthogonal subspace pursuit (OSP). …”
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Modeling and Reconstruction of Mixed Functional and Molecular Patterns

“…Formulating the task as a blind source separation or composite signal factorization problem, we report here a statistically principled method for modeling and reconstruction of mixed functional or molecular patterns. The computational algorithm is based on a latent variable model whose parameters are estimated using clustered component analysis. …”
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Analyzing the applicability of psychometric QoE modeling for projection-based point cloud video quality assessment by Sam Van Damme, Jeroen van der Hooft, Filip De Turck, Maria Torres Vega

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Modeling and Reconstruction of Mixed Functional and Molecular Patterns by Yue Wang, Jianhua Xuan, Rujirutana Srikanchana, Peter L. Choyke

“…Formulating the task as a blind source separation or composite signal factorization problem, we report here a statistically principled method for modeling and reconstruction of mixed functional or molecular patterns. The computational algorithm is based on a latent variable model whose parameters are estimated using clustered component analysis. …”
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Multiclass Sparse Bayesian Regression for fMRI-Based Prediction by Vincent Michel, Evelyn Eger, Christine Keribin, Bertrand Thirion

“…We detail these framework and validate our algorithm on simulated and real neuroimaging data sets, showing that it performs better than reference methods while yielding interpretable clusters of features.…”
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