An Empirical Taxonomy of Video Summarization Model From a Statistical Perspective by Sai Babu Veesam, Aravapalli Rama Satish

“…This paper has thrown out a comprehensive taxonomic view of all different video summarization techniques that show variously adopted methodologies efficiently condensing large video data. …”
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A Comprehensive Review on Sensor-Based Electronic Nose for Food Quality and Safety by Teodora Sanislav, George D. Mois, Sherali Zeadally, Silviu Folea, Tudor C. Radoni, Ebtesam A. Al-Suhaimi

“…Our review found that most of the efforts use portable, low-cost electronic noses, coupled with pattern recognition algorithms, for evaluating the quality levels in certain well-defined food classes, reaching accuracies exceeding 90% in most cases. …”
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Classification of Structural and Functional Development Stage of Cardiomyocytes Using Machine Learning Techniques by V. R. Bondarev, K. O. Ivanko, N. G. Ivanushkina

“…A pre-processed and augmented dataset is used for training of the convolutional neural network having an architecture with hierarchical structure and residual block usage. The model is evaluated based on the confusion matrix and the heat maps of different convolutional layers are analyzed. …”
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Physical Information Neural Network-Based Seepage Behavior Analysis of Earth and Rock Dams by XUE binghan, HUANG zhenhua, LEI Jianwei, FANG Hongyuan

“…Furthermore, for complex earth-rock dam problems involving non-homogeneous materials, the algorithm maintains stable solutions with high accuracy, confirming its adaptability to intricate engineering challenges. …”
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A Biologically Inspired Program-Level Imitation Approach for Robots by Pourya Aliasghari, Moojan Ghafurian, Chrystopher L. Nehaniv, Kerstin Dautenhahn

“…To learn a new task, human-provided demonstrations—obtained by a robot through different modalities such as kinesthetic teaching or behavioural observation—are processed by an algorithm to discover multiple possible arrangements of sub-goals that achieve the task goal. …”
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Comparison of methods for tuning machine learning model hyper-parameters: with application to predicting high-need high-cost health care users by Christopher Meaney, Xuesong Wang, Jun Guan, Therese A. Stukel

“…For each HPO method, we estimated 100 extreme gradient boosting models at different hyper-parameter configurations; and evaluated model performance using an AUC metric on a randomly sampled validation dataset. …”
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Snoring Sound Recognition Using Multi-Channel Spectrograms by Ziqiang YE, Jianxin PENG, Xiaowen ZHANG, Lijuan SONG

“…This paper proposes a snoring sound detection algorithm using a multi-channel spectrogram and convolutional neural network (CNN). …”
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Dual-stream interactive mechanism with multi-modal hierarchical aggregation transformer for gait recognition by Jinghang Liu, Xiangyuan Xu, Yan Qiu, Chunzhi Wang

“…When processing multimodal data, existing algorithms frequently encounter challenges such as integration difficulties and insufficient fusion due to data heterogeneity across different modalities. …”
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Temporal scalability analysis of spectral remote sensing and Machine Learning-Based models for forest mapping in the tropical region of Nigeria by K. Pawłuszek-Filipiak, D. Włodarczyk, K. Stuchły, F.E. Ikuemonisan

“…To address this challenge, the study recommends prioritizing adaptive modeling strategies. These strategies involve continuously updating and retraining ML-RS models to ensure they remain accurate over different periods, thereby improving the reliability of forest mapping over time. …”
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Employing Streaming Machine Learning for Modeling Workload Patterns in Multi-Tiered Data Storage Systems by Edson Ramiro Lucas Filho, George Savva, Lun Yang, Kebo Fu, Jianqiang Shen, Herodotos Herodotou

“…Modern multi-tiered data storage systems optimize file access by managing data across a hybrid composition of caches and storage tiers while using policies whose decisions can severely impact the storage system’s performance. Recently, different Machine-Learning (ML) algorithms have been used to model access patterns from complex workloads. …”
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MRFB-Net: A Novel Attention Pooling Network With Modified Receptive Field Block for Uterine Fibroid Segmentation by Yun Jiang, Xiaokang Ding, Hongmei Zhou

“…The evaluation results demonstrate the accuracy and reliability of the proposed MRFB-Net, as well as its adaptability to different types of medical images. …”
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All-Digital Timing Recovery for Free Space Optical Communication Signals With a Large Dynamic Range and Low OSNR by Yunfeng Gu, Sheng Cui, Changjian Ke, Keji Zhou, Deming Liu

“…For this reason flexible digital coherent receivers (DCR) capable of adapting to different channel conditions have attracted much attention in the FSOC field. …”
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Ranking Assisted Unsupervised Morphological Disambiguation of Turkish by Hayri Volkan Agun, Ozkan Aslan

“…Furthermore, to reduce ambiguity in sentences from different genres with scarce samples, the proposed method is easily adaptable.…”
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Multimodal dataset for sensor fusion in fall detection by Carla Taramasco, Miguel Pineiro, Pablo Ormeño-Arriagada, Diego Robles, David Araya

“…Our research introduces a novel multisensor dataset designed to support the creation and evaluation of advanced multisensor fall detection algorithms. …”
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Analysis of Blockchain-Technology by Danylo Dvorchuk, Iryna Shpinareva

“…The study explores the comparative advantages and limitations of different blockchain architectures and evaluates emerging optimization techniques such as hybrid consensus algorithms and artificial intelligence-based enhancements. …”
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FQDNet: A Fusion-Enhanced Quad-Head Network for RGB-Infrared Object Detection by Fangzhou Meng, Aoping Hong, Hongying Tang, Guanjun Tong

“…To improve multi-scale feature utilization, we designed the Dynamic-Weight-based Quad-Head Detector (DWQH), which dynamically assigns weights to different scales, enabling adaptive fusion and enhancing multi-scale feature representation. …”
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Log-Based Analysis of Creativity in the Context of Computational Thinking by Rotem Israel-Fishelson, Arnon Hershkovitz

“…We took a learning analytics log-based approach to evaluate measures of CT and creativity. We developed a Python algorithm to automatically analyze the logged solutions across four creativity measures. …”
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Reinforcement-Learning-Based Edge Offloading Orchestration in Computing Continuum by Ioana Ramona Martin, Gabriel Ioan Arcas, Tudor Cioara

“…We have chosen the Deep Q-Learning algorithm and adapted it to our workload offloading problem. …”
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Machine learning based method for forecasting short-term passenger flow in urban rail stations by HU Mingwei, SHI Xiaolong, WU Wenlin, HE Guoqing

“…However, the single model has poor adaptability to different types of subway stations. Compared with a single model, LightGBM-LSTM model equipped with merits of multiple models, fulfills a better function in forecasting and a better adaptability to different types of urban rail transit stations.…”
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SegMatch: semi-supervised surgical instrument segmentation by Meng Wei, Charlie Budd, Luis C. Garcia-Peraza-Herrera, Reuben Dorent, Miaojing Shi, Tom Vercauteren

“…For binary segmentation tasks, our algorithm was evaluated on the MICCAI Instrument Segmentation Challenge datasets, Robust-MIS 2019 and EndoVis 2017. …”
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