Comparative Analysis between Active Contour and Otsu Thresholding Segmentation Algorithms in Segmenting Brain Tumor Magnetic Resonance Imaging by Sarah Husham, Aida Mustapha, Salama A. Mostafa, Mohammed K. Al-Obaidi, Mazin Mohammed, Alyaa Idrees Abdulmaged, S. Thomas George

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Improve unsupervised Learning-based landslides detection by band ratio processing of RGB optical images: a case study on rainfall-induced landslide clusters by Lichuan Chen, Xuekun Xiang, Haijia Wen, Jiafeng Xiao, Chenhao Song, Xinzhi Zhou, Jingyuan Yu

“…Then, by further optimizing the relevant parameters, the threshold-based Image Difference and Principal Component Analysis-based K-means unsupervised learning classification methods are used to perform change detection and landslide cluster identification. …”
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Content-aware image resizing based on random-carving with probability by Ying-chun GUO, Jun-teng HOU, Ming YU, Rui-li WANG

Subjects: “…threshold learning…”
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Collectivist values help solve the climate dilemma by Riccardo Pansini, Riccardo Pansini, Lei Shi, Lei Shi

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Content-aware image resizing based on random-carving with probability by Ying-chun GUO, Jun-teng HOU, Ming YU, Rui-li WANG

Subjects: “…threshold learning;radial basis function;random-carving with probability;rapid content-aware image resizing…”
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The relationship between passive social network site use and sub-threshold depression among college students: a moderated mediation model by Jiangli Jiao, Xiaojuan Dong, Nuziyan Nuermaimaiti, Yi Liu

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Establishing radar-derived rainfall thresholds for a landslide early warning system: a case study in the Sichuan Basin, Southwest China by Pinliang Li, Qiang Xu, Jialiang Liu, Fulin Zhang, Xu Ji, Dalei Peng, Chuanhao Pu, Wanlin Chen, Shuang Yuan, Chaoyang He

“…This study aims to establish reliable empirical rainfall thresholds for the landslide early warning systems (LEWSs) in the study area, utilizing radar-derived rainfall data processed by deep learning. …”
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Alzheimer’s Disease Detection Using Deep Learning and Federated Learning by Taha Bin Niaz, Usman Amjad, Humera

“…The goal of this paper is to defend sensitive patient data by proposing a deep learning algorithm that utilizes Federated learning techniques in an IoT-based edge computing framework. …”
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Threshold-Free Symbol Decision Based on Spatial 4PPM Correlation for Uplink Screen Camera Communication Using Low-Luminance SDM Screen by Alisa Kawade, Wataru Chujo, Kentaro Kobayashi

“…Since the low-luminance pixels on the screen are affected by ambient light, it is difficult to determine each cell symbol correctly using pre-trained pixel value threshold. To make symbol decisions without threshold learning, symbol decisions based on correlation of spatial 4 pulse position modulation (4PPM) pattern are demonstrated with numerical models and experiments. …”
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A novel dynamic weighted prediction framework with stability-enhanced dynamic thresholding feature selection for neurodegenerative disease detection using gait features by Diksha Giri, Ranjit Panigrahi, Samrat Singh Bhandari, Moumita Pramanik, Akash Kumar Bhoi, Victor Hugo C. de Albuquerque

“…Cognitive bias might hinder clinical assessments and early detection. Machine learning may help detect aberrant gait patterns early. …”
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AI-driven skin cancer detection from smartphone images: A hybrid model using ViT, adaptive thresholding, black-hat transformation, and XGBoost. by Adil El Mertahi, Hind Ezzine, Samira Douzi, Khadija Douzi

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Artificial intelligence in data storage systems by V. V. Zhilin, O. A. Safar'yan

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Regional landslide hazard assessment using the IV-RF coupling model and critical monthly average rainfall threshold：A case study from Fuling District, Chongqing by Shuangqing PENG, Pengfei LIU, Gang CHEN, Liping WANG, Wei ZHANG, Wenwen LUO, Xiliang JING

“…The results show that coupling the Information Value and machine learning models compensates for the shortcomings of machine learning in early data input and non-sample selection, enhancing the predictive accuracy of single machine learning models. …”
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A hybrid machine learning framework by incorporating categorical boosting and manifold learning for financial analysis by Yuyang Zhao, Hongbo Zhao

“…This study developed a hybrid machine-learning framework incorporating categorical boosting (CatBoost) and manifold learning for financial analysis. …”
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Machine learning electroweakino production by Rafał Masełek, Mihoko M. Nojiri, Kazuki Sakurai

“…In this study, we explore Machine Learning (ML) methods for efficient signal/background discrimination. …”
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Aerodynamic Parameter Identification of Projectile Based on Improved Extreme Learning Machine and Ensemble Learning Theory by Tianyi Wang, Wenjun Yi, Youran Xia

“…The improved particle swarm optimization algorithm (IPSO) with an adaptive update strategy is used to optimize the weight and threshold of ELM. Combined with the ensemble learning theory, the improved ELM neural network is regarded as a weak learner to generate a strong learner. …”
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The Impact of Policy Thematic Differences on Industrial Development: An Empirical Study Based on China’s Electric Vehicle Industry Policies at the Central and Local Levels by Zizheng Liu, Tao Xie

“…This study adopted a central–local policy interaction perspective, employing the BERT deep semantic learning model and a threshold regression model to investigate the impact of policy differences on industrial development. …”
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Rainfall-induced Landslide Susceptibility Prediction Considering Spatial Heterogeneity by ZHANG Xingfu, JIANG Yuanjun, ABI Erdi

Subjects: “…Mixed distribution rainfall threshold…”
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Modeling of spatial extremes in environmental data science: time to move away from max-stable processes by Raphaël Huser, Thomas Opitz, Jennifer L. Wadsworth

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Neural spiking for causal inference and learning. by Benjamin James Lansdell, Konrad Paul Kording

“…When a neuron is driven beyond its threshold, it spikes. The fact that it does not communicate its continuous membrane potential is usually seen as a computational liability. …”
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