How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation by Joni Salminen (7434770)

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Detecting latent classes in tourism data through response-based unit segmentation (REBUS) in Pls-Sem by Assaker, Guy

“…This research note describes Response-Based Unit Segmentation (REBUS), a “latent class detection” technique used in partial least squares–structural equation modeling (PLS-SEM) to examine data heterogeneity. …”
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A multi-pretraining U-Net architecture for semantic segmentation by Cagla Copurkaya (22502042)

“…New developments in the deep learning field contributed to the development of new application domains and this has made segmenting nuclei possible. In this research, we propose and evaluate a modified version of a deep learning algorithm called U-Net architecture for partitioning histopathological images. …”

VEGAWES: variational segmentation on whole exome sequencing for copy number detection by Samreen Anjum (19651882)

“…In this work, we developed VEGAWES for accurate and robust detection of copy number variations on WES data. VEGAWES is an extension to a variational based segmentation algorithm, VEGA: Variational estimator for genomic aberrations, which has previously outperformed several algorithms on segmenting array comparative genomic hybridization data. …”

Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units by Shanableh, Tamer

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Towards Multimedia Fragmentation by Saad, Samir

“…Database fragmentation is a process for reducing irrelevant data accesses by grouping data frequently accessed together in dedicated segments. …”
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Left Ventricular Wall Motion Estimation by Active Polynomials for Acute Myocardial Infarction Detection by Serkan Kiranyaz (3762058)

A Novel Non-Invasive Estimation of Respiration Rate From Motion Corrupted Photoplethysmograph Signal Using Machine Learning Model by Md. Nazmul Islam Shuzan (16888827)

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The use of semantic-based predicates implication to improve horizontal multimedia database fragmentation by Getahun, Fekade

“…Database fragmentation allows reducing irrelevant data accesses by grouping data frequently accessed together in dedicated segments. …”
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DoFP-ML: A Machine Learning Approach to Food Quality Monitoring Using a DoFP Polarization Image Sensor by Maen Takruri (10873368)

Damage assessment & recovery from malicious transactions using data dependency for deffensive information warfare. (c2006) by Zeitunlian, Arda

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MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network by Sakib Mahmud (15302404)

Using Data Mining in CRM to Understand the Insurance Market by Qadadeh, Wafa

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Big Data Energy Management, Analytics and Visualization for Residential Areas by Gupta, Ragini

“…Utilizing the same common communication infrastructure, it also allows the utilities on different consumption levels (community, state, country) to monitor and visualize the energy consumption in their respective grid segments on daily, monthly, and yearly basis. A high-speed distributed computing cluster based on commodity hardware with efficient big data mathematical algorithm is employed in this work. …”
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Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

“…The automatic segmentation algorithm is adopted to extract the region of interest, and subsequently morphological and texture features are computed. …”

Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …”

Damage assessment and recovery from malicious transactions using data dependency for defensive information warfare by Haraty, Ramzi A.

“…Since even segmenting the log into clusters may not solve the problem, as clusters/segments may grow to be humongous in size, this is in case of high data/transaction dependency, we suggest a method for segmenting the log into clusters and its sub-clusters; i.e, segmenting the cluster; based on exact data dependency [12], into sub-clusters; based on two different criteria: number of data items or space occupied. …”
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Identifying Regional Trends in Avatar Customization by Peter Mawhorter (18602944)

Large-scale annotation dataset for fetal head biometry in ultrasound images by Mahmood Alzubaidi (15740693)

“…For enhanced compatibility and usability, the dataset is available in 11 universally accepted formats, including Cityscapes, YOLO, CVAT, Datumaro, COCO, TFRecord, PASCAL, LabelMe, Segmentation mask, OpenImage, and ICDAR. This broad range of formats ensures adaptability for various computer vision tasks, such as classification, segmentation, and object detection. …”

Finetuning Analytics Information Systems for a Better Understanding of Users: Evidence of Personification Bias on Multiple Digital Channels by Bernard J. Jansen (7434779)

“…<p dir="ltr">Although the effect of hyperparameters on algorithmic outputs is well known in machine learning, the effects of hyperparameters on information systems that produce user or customer segments are relatively unexplored. …”