Counting sheep: human experience vs. Yolo algorithm with drone to determine population by Jordan Ninahuanca Carhuas, Luigüi Andre Cerna Grados, Ide Unchupaico Payano, Edgar Garcia-Olarte, Yakelin Mauricio-Ramos, Carlos Quispe Eulogio, Mohamed M. Hadi Mohamed

“…Further improvements in algorithm training and computational resources could enhance the algorithm's accuracy. …”
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Determination of sugar in tangerines by fluorescence with an Improved partial least squares (PLS) algorithm by Lei Liu, Chunzhong Li, Haiyi Bian, Ahmed N Abdalla, Hua Yao, Wen Li

“…The training dataset was evaluated using cross-validation, and F -values were computed to determine how many main components should be utilized to build the model. …”
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Detecting Pronunciation Errors in Spoken English Tests Based on Multifeature Fusion Algorithm by Yinping Wang

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Performance Comparison of Random Forest and Decision Tree Algorithms for Anomaly Detection in Networks by Rafiq Fajar Ramadhan, Wahid Miftahul Ashari

“…The data collection method, pre-processing, data splitting and modelling using SMOTE method to handle data imbalanced were applied in both algorithms and then evaluated using accuracy, precision, recall and f1-score metrics. …”
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Identification of Perceptual Phonetic Training Gains in a Second Language Through Deep Learning by Georgios P. Georgiou

“…This study addresses this gap by developing a deep learning algorithm designed to identify perceptual gains resulting from second language (L2) phonetic training. …”
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Development of a software platform for automatic train operation: Integrating meso- and microscopic layers by Daniel Bilbao-Moreno, Iker Elorza, Eloy Irigoyen

“…A key outcome of this research is developing a software platform that provides the foundation for improving autonomous train control algorithms. The mesoscopic layer, defined as the high-level component of the automatic train operation (ATO) subsystem, focuses on generating setpoints to control the traction system, which are subsequently transmitted to the low-level component of the ATO subsystem. …”
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Disease Detection in Tomato Fruit Using Deep Learning Algorithms: Comparative Analysis by Fatma Feyza Akyol, Ayhan İstanbullu, Faruk Özel

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Analysis of Tire-Pavement Contact Morphology Characteristics during the Virtual Track Train Maneuvering by Chengping Wang, Jimin Zhang, Hechao Zhou

“…This research can be used to evaluate and analyze the response and damage of the virtual track train to asphalt pavement under uniform, braking, and cornering conditions. …”
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FlightScope: An Experimental Comparative Review of Aircraft Detection Algorithms in Satellite Imagery by Safouane El Ghazouali, Arnaud Gucciardi, Francesca Venturini, Nicola Venturi, Michael Rueegsegger, Umberto Michelucci

“…This paper critically evaluates and compares a suite of advanced object detection algorithms customized for the task of identifying aircraft within satellite imagery. …”
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A Comparative Study of Data-Driven Prognostic Approaches under Training Data Deficiency by Jinwoo Song, Seong Hee Cho, Seokgoo Kim, Jongwhoa Na, Joo-Ho Choi

“…While the data-driven approach is the most common for this purpose, they often face challenges due to insufficient training data. This study delves into the prognostic capabilities of four methods under the conditions of limited training datasets. …”
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HI-TAM, a hybrid intelligence framework for training and adoption of generative design assistants by Yaoli Mao, Janet Rafner, Janet Rafner, Yi Wang, Jacob Sherson

“…Culminating in the HI-TAM, our contribution to human-AI interaction is 4-fold including (i) domain-specific suitability of the HI approach for real-world application design, (ii) a programmable common language that facilitates the clear communication of expert design goals to the generative algorithm, (iii) a human-centered continual training loop that seamlessly integrates AI training into the expert's workflow, (iv) a hybrid intelligence narrative that encourages the psychological willingness to invest time and effort in training a virtual assistant. …”
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Robust Classification of UWB NLOS/LOS Using Combined FCE and XGBoost Algorithms by Shoude Wang, Nur Syazreen Ahmad

“…Preliminary NLOS identification and classification are performed using Fuzzy Comprehensive Evaluation (FCE), with subsequent optimization of FCE weights via the Pattern Search algorithm (PSa). …”
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Robust Adversarial Example Detection Algorithm Based on High-Level Feature Differences by Hua Mu, Chenggang Li, Anjie Peng, Yangyang Wang, Zhenyu Liang

“…A range of detection algorithms has been developed to differentiate between benign samples and adversarial examples. …”
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Ultrasound thyroid nodule segmentation algorithm based on wavelet transform and CNN-Transformer by ZHENG Shuijing, YANG Jun, CAI Yujiao

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Automated Food Weight and Content Estimation Using Computer Vision and AI Algorithms by Bryan Gonzalez, Gonzalo Garcia, Sergio A. Velastin, Hamid GholamHosseini, Lino Tejeda, Gonzalo Farias

“…An RGB camera is employed to capture the tray delivery process in a self-service restaurant, providing test images for plate counting and content identification algorithm comparison, using standard evaluation metrics. …”
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Predicting Dilution in Underground Mines with Stacking Artificial Intelligence Models and Genetic Algorithms by Jorge L. V. Mariz, Tertius S. G. Ferraz, Marinésio P. Lima, Ricardo M. A. Silva, Hyongdoo Jang

“…A total of eight supervised machine learning algorithms were investigated, with their hyperparameters systematically optimized using two distinct genetic algorithm (GA) strategies evaluated under varying population sizes. …”
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Deep learning and fuzzy algorithm in improving the effectiveness of college English translation teaching by Biao Kong, Che He

“…Based on the data analysis of 387 students, the BiLSTM model is used to train translation tasks, and the fuzzy inference system is used to evaluate translation quality comprehensively. …”
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Quantitative benchmarking of nuclear segmentation algorithms in multiplexed immunofluorescence imaging for translational studies by Abishek Sankaranarayanan, Georgii Khachaturov, Kimberly S. Smythe, Shachi Mittal

“…Pre-trained deep learning models outperform classical nuclear segmentation algorithms. …”
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Leveraging ECG images for predicting ejection fraction using machine learning algorithms by Abhyuday Kumara Swamy, Vivek Rajagopal, Deepak Krishnan, Paramita Auddya Ghorai, Anagha Choukhande, Santhosh Rathnam Palani, Deepak Padmanabhan, Emmanuel Rupert, Devi Prasad Shetty, Pradeep Narayan

“…Introduction: The capability to accurately predict the ejection fraction (EF) from an electrocardiogram (ECG) holds significant and valuable clinical implications. Various algorithms based on ECG images are currently being evaluated, with most methods requiring raw signal data from ECG devices. …”
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Idiographic Lapse Prediction With State Space Modeling: Algorithm Development and Validation Study by Eric Pulick, John Curtin, Yonatan Mintz

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