Hyperparameter tuned deep learning-driven medical image analysis for intracranial hemorrhage detection. by Naif Almakayeel, E Laxmi Lydia, Oleg Razzhivin, S Rama Sree, Mohammed Altaf Ahmed, Bibhuti Bhusan Dash, S P Siddique Ibrahim

“…Lastly, the Bayesian optimizer algorithm (BOA) is implemented for the hyperparameter selection of the DL technique. …”
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Reinforcement Learning for Reconfigurable Robotic Soccer by M. Shameer Ahamed, J. J. J. Pey, S. M. Bhagya P. Samarakoon, M. A. Viraj J. Muthugala, Mohan Rajesh Elara

“…Robotic soccer is becoming more prevalent in competitions, furthering research in robotics and artificial intelligence. Reconfigurable robotics is used in application domains such as cleaning, multi-terrain locomotion, and logistical support, but reconfigurability has yet to be introduced in robotic soccer. …”
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Achieving precision assessment of functional clinical scores for upper extremity using IMU-Based wearable devices and deep learning methods by Weinan Zhou, Diyang Fu, Zhiyu Duan, Jiping Wang, Linfu Zhou, Liquan Guo

“…The application of the proposed method enables precision assessment of patients’ upper extremity motor function, thereby facilitating more personalized rehabilitation programs to achieve optimal recovery outcomes. Trial registration: Clinical trial of telerehabilitation training and intelligent evaluation system, ChiCTR2200061310, Registered 20 June 2022-Retrospective registration.…”
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Integrated remote sensing, machine learning and geospatial approach for site selection of sewage treatment plants in the metropolitan city by S. Rajalakshmi, S. Subathradevi, Abdulaziz G. Alghamdi, Hadeel Alsolai

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Overheating Defect Detection of Composite Insulator Based on Mask R-CNN by Yi GAO, Lianfang TIAN, Qiliang DU

“…Aiming at the problems of large workload and low intelligence of the current infrared image-based overheating defect detection techniques for composite insulators, and the poor accuracy and poor generalization performance of the traditional image segmentation methods in complex backgrounds, an overheating defect detection method is proposed for composite insulators based on instance segmentation network Mask R-CNN. …”
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Integrating Positron Emission Tomography Combined with Computed Tomography Imaging into Advanced Radiation Therapy Planning: Clinical Applications, Innovations, and Challenges by Subhash Chand Kheruka, Anjali Jain, M. Sharjeel Usmani, Naema Al-Maymani, Noura Al-Makhmari, Huda Al-Saidi, Sana Al-Rashdi, Anas Al-Balushi, Vipin Jayakrishnan, Khulood Al-Riyami, Rashid Al-Sukaiti, Raza Sayani

“…We examine advanced methodologies such as deformable image registration, radiomics, and artificial intelligence (AI)-driven segmentation for their potential to reduce interobserver variability and streamline radiotherapy (RT) workflows. …”
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Non-contact measurement method of three-phase cable voltage based on inverse calculation of electric field by ZHANG Songhui, CHEN Zijian, MA Chaojun, CHEN Qing, LIU Tao, TAN Yekui

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Structural design, modeling and simulation analysis of a cage broiler inspection robot by Yongmin Guo, Xinwei Yu, Wanchao Zhang, Changxi Chen, Liji Yu

“…By integrating energy-efficient design principles and intelligent control strategies, the lifting and lowering functions of the system can reduce energy consumption. …”
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Challenges Faced by Clinicians in the Personalized Treatment Planning: A Literature Review and the First Results of the Russian National Cancer Program by P. V. Shegai, P. A. Shatalov, A. A. Zabolotneva, N. A. Falaleeva, S. A. Ivanov, A. D. Kaprin

“…In this report, we consider the key characteristics for planning an optimal clinical treatment regimen and which should be included in the algorithm of clinical decision support systems. …”
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Small Scale Multi-Object Segmentation in Mid-Infrared Image Using the Image Timing Features–Gaussian Mixture Model and Convolutional-UNet by Meng Lv, Haoting Liu, Mengmeng Wang, Dongyang Wang, Haiguang Li, Xiaofei Lu, Zhenhui Guo, Qing Li

“…The application of intelligent video monitoring for natural resource protection and management has become increasingly common in recent years. …”
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Tea Disease Detection Method Based on Improved YOLOv8 in Complex Background by Junchen Ai, Yadong Li, Shengxiang Gao, Rongsheng Hu, Wengang Che

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Computational-Based Approaches for Predicting Biochemical Oxygen Demand (BOD) Removal in Adsorption Process by Mohamed K. Mostafa, Ahmed S. Mahmoud, Mohamed S. Mahmoud, Mahmoud Nasr

“…Results indicated that the medium pH and adsorption time should be adjusted around 7 and 30 min, respectively, to maintain the highest BOD removal efficiency of 96.4% at initial BOD concentration Co=100 mg/L, mixing rate=200 rpm, and adsorbent dosage of 3 g/L. An optimized ANN structure of 5–10–1, with the “trainlm” back-propagation learning algorithm, achieved the highest predictive performance for BOD removal (R2: 0.972, Adj-R2: 0.971, RMSE: 1.449, and SSE: 56.680). …”
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SwinFishNet: A Swin Transformer-based approach for automatic fish species classification using transfer learning. by Ebru Ergün

“…Transfer learning was applied using the ST, which was fine-tuned on these datasets and optimized with the AdamW algorithm. The model's performance was evaluated using classification accuracy (CA), F1-score, recall, precision, Matthews correlation coefficient, Cohen's kappa and confusion matrix metrics. …”
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ARIMA-Kriging and GWO-BiLSTM Multi-Model Coupling in Greenhouse Temperature Prediction by Wei Zhou, Shuo Liu, Junxian Guo, Na Liu, Zhenglin Li, Chang Xie

“…Utilizing the high-quality data processed by this model, this study proposes and constructs a novel Grey Wolf Optimizer and Bidirectional Long Short-Term Memory (GWO-BiLSTM) temperature prediction framework, which combines a Grey Wolf Optimizer (GWO)-enhanced algorithm with a Bidirectional Long Short-Term Memory (BiLSTM) network. …”
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Machine learning-based estimation of seismic structural damage via an accessible web application by Vasile Calofir, Mircea-Ștefan Simoiu, Ruben-Iacob Munteanu, Emil Calofir, Sergiu-Stelian Iliescu

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Predicting hydrocarbon reservoir quality in deepwater sedimentary systems using sequential deep learning techniques by Xiao Hu, Jun Xie, Xiwei Li, Junzheng Han, Zhengquan Zhao, Hamzeh Ghorbani

“…Three sequential deep learning models—Recurrent Neural Network and Gated Recurrent Unit—were developed and optimized using the Adam algorithm. The Adam-LSTM model outperformed the others, achieving a Root Mean Square Error of 0.009 and a correlation coefficient (R2) of 0.9995, indicating excellent predictive performance. …”
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Lightweight deep neural network for contour detection and extraction of wheat spikes in complex field environments by Xin Xu, Haiyang Zhang, Jiangchuan Lu, Ziyi Guo, Juanjuan Zhang, Jibo Yue, Hongbo Qiao, Xinming Ma

“…This method not only enables precise spike phenotyping but also provides robust algorithmic support for intelligent field spikelet counting systems, advancing translational applications in crop phenomics.…”
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Reversible Adversarial Examples with Minimalist Evolution for Recognition Control in Computer Vision by Shilong Yang, Lu Leng, Ching-Chun Chang, Chin-Chen Chang

“…To achieve zero-bit error restoration, we utilize the differential evolution algorithm to optimize adversarial perturbations while minimizing distortion. …”
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Fostering non-intrusive load monitoring for smart energy management in industrial applications: an active machine learning approach by Lukas Fabri, Daniel Leuthe, Lars-Manuel Schneider, Simon Wenninger

“…To overcome this issue, we develop an active learning model using real-world data to intelligently select the most informative data for expert labeling. …”
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Precision Medicine in Lung Cancer Screening: A Paradigm Shift in Early Detection—Precision Screening for Lung Cancer by Hsin-Hung Chen, Yun-Ju Wu, Fu-Zong Wu

“…However, implementation must also address challenges related to health equity, algorithmic bias, and system integration. As precision medicine continues to evolve, it holds the promise of optimizing early detection, minimizing harm, and extending the benefits of lung cancer screening to broader and more diverse populations. …”
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