On-Device System for Device Directed Speech Detection for Improving Human Computer Interaction by Abhishek Singh, Rituraj Kabra, Rahul Kumar, Manjunath Belgod Lokanath, Reetika Gupta, Sumit Kumar Shekhar

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fossilbrush: An R package for automated detection and resolution of anomalies in palaeontological occurrence data by Joseph T. Flannery‐Sutherland, Nussaïbah B. Raja, Ádám T. Kocsis, Wolfgang Kiessling

“…There are also no standardised methods to detect and resolve errors despite the development of an ecosystem of cleaning tools fuelled by the concurrent growth of neontological occurrence databases. …”
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On the black-box explainability of object detection models for safe and trustworthy industrial applications by Alain Andres, Aitor Martinez-Seras, Ibai Laña, Javier Del Ser

“…However, their adoption in high-risk applications, where errors may cause severe consequences, remains limited. …”
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Adaptive path planning for efficient object search by UAVs in agricultural fields by Rick van Essen, Eldert van Henten, Lammert Kooistra, Gert Kootstra

“…We evaluated the effect of different detection certainty measures, optimized the path planning parameters, investigated the effects of localization errors, and different numbers of objects in the field. …”
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Hydropower Station Status Prediction Using RNN and LSTM Algorithms for Fault Detection by Omar Farhan Al-Hardanee, Hüseyin Demirel

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An Integrated Framework for Cryptocurrency Price Forecasting and Anomaly Detection Using Machine Learning by Hani Alnami, Muhammad Mohzary, Basem Assiri, Hussein Zangoti

“…The deep learning model indicates strong generalization capabilities, suggesting potential advantages on more complex datasets. These findings highlight the importance of combining advanced machine learning techniques and cryptocurrencies to develop a robust framework for cryptocurrency forecasting and anomaly detection.…”
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A Secure and Robust Machine Learning Model for Intrusion Detection in Internet of Vehicles by Pradeep Kumar Tiwari, Shiv Prakash, Animesh Tripathi, Tiansheng Yang, Rajkumar Singh Rathore, Manish Aggarwal, Narendra Kumar Shukla

“…The experimental findings demonstrate the superior performance of the proposed model in detecting and classifying intrusions within IoV.…”
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Tree Top Detection in UAV Data: Evaluating Accuracy of Different Estimation Techniques by A. Hosingholizade, Y. Erfanifard, Y. Erfanifard, S. K. Alavipanah, V. García Millan, S. Pirasteh, S. Pirasteh, A. N. Arslan, A. N. Arslan

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Automatic Detection of Interplanetary Coronal Mass Ejections in Solar Wind In Situ Data by H. T. Rüdisser, A. Windisch, U. V. Amerstorfer, C. Möstl, T. Amerstorfer, R. L. Bailey, M. A. Reiss

“…Our pipeline manages to find the start of an ICME with a mean absolute error (MAE) of around 2 hr and 56 min, and the end time with a MAE of 3 hr and 20 min. …”
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Automated concrete exposed reinforcement and corrosion detection and measurement using coloured illumination by Dow Hamish, Darby Andrew, Perry Marcus, Zhang Feng

“…Additionally, the algorithm’s corrosion surface area measurements produced a maximum relative error of negative 8 %. These findings demonstrate how colour-controlled illumination can enhance visual inspections, leading to more efficient monitoring and improved durability of reinforced concrete structures.…”
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Quaternion Signal Analysis for Detection of Broken Rotor Fault Degrees in Induction Motors by Jose Luis Contreras-Hernandez, Dora Luz Almanza-Ojeda, Rogelio Castro-Sanchez, Mario Alberto Ibarra-Manzano

“…Fault detection in induction motors is essential for maintaining the reliability of industrial operations. …”
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Zero-Shot Automated Detection of Fake News: An Innovative Approach (ZS-FND) by Rania Baashirah

“…These findings highlight the potential of ZSL models in providing a more robust and efficient solution for FND.…”
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A Comparison Between Artificial Intelligence and Radiologists’ Ability to Detect Lung Nodules by Cristina Mihaela CIOFIAC, Rossy Vlăduţ TEICĂ, Lucian Mihai FLORESCU, Ioana Andreea GHEONEA

“…Conclusions: Artificial Intelligence-assisted reading has proven superior to unaided radiologist evaluation in detecting lung nodules. These findings support the potential of AI-powered systems as valuable tools in clinical practice, complementing radiologists’ expertise. …”
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Integrating ANN and ANFIS for effective fault detection and location in modern power grid by Yadav Goutam Kumar, Kirar Mukesh Kumar, Gupta S.C., Rajender Jatoth

“…Results demonstrate that the ANFIS-based approach achieves high accuracy in fault detection and classification, significantly reducing the response time. …”
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Research on plasma arc flame length detection technology based on region of interest. by Jie Li, Wei Jiang, Jian Lei, Xiaoxiao Xing

“…The corrected plasma arc length averages around 40mm, with a detection error of less than 1mm when compared to the desired controlled plasma arc length. …”
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Impacts of Spatial and Temporal Resolution on Remotely Sensed Corn and Soybean Emergence Detection by Feng Gao, Martha Anderson, Rasmus Houborg

“…However, the 30 m HLS lacked sub-field details in fields with mixed cropping systems. The findings from this study could benefit remotely sensed crop emergence detection from local to regional scales.…”
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Robust Image Steganography Approach Based on Edge Detection Combined With CNN Algorithm by Rana Al-Rawashdeh, Md Mahfuzur Rahman, Mahmood Niazi

“…The main problem in image steganography is to find the right balance between the maximum amount of secret data that can be transmitted or stored in the cover image and the quality of the stego image to make the secret data un-noticeable to human senses or other detection mechanisms. …”
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Advanced deep transfer learning techniques for efficient detection of cotton plant diseases by Prashant Johri, SeongKi Kim, Kumud Dixit, Prakhar Sharma, Barkha Kakkar, Yogesh Kumar, Jana Shafi, Muhammad Fazal Ijaz

“…Additionally, deep learning has begun as a powerful technique for to detect diseases in crops using images. Hence, the significance of this work lies in its potential to mitigate the impact of these diseases, which cause significant damage to the cotton and decrease fibre quality and promote sustainable agricultural practices.MethodsThis paper investigates the role of deep transfer learning techniques such as EfficientNet models, Xception, ResNet models, Inception, VGG, DenseNet, MobileNet, and InceptionResNet for cotton plant disease detection. …”
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AI-enabled driver assistance: monitoring head and gaze movements for enhanced safety by Sayyed Mudassar Shah, Gan Zengkang, Zhaoyun Sun, Tariq Hussain, Khalid Zaman, Abdullah Alwabli, Amar Y. Jaffar, Farman Ali

“…Finally, the implications of these findings are discussed, and potential avenues for future research are outlined.…”
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The Advanced Reasoning Capabilities of Large Language Models for Detecting Contraindicated Options in Medical Exams by Yuichiro Yano, Mizuki Ohashi, Taiju Miyagami, Hirotake Mori, Yuji Nishizaki, Hiroyuki Daida, Toshio Naito

“… AbstractEnhancing clinical reasoning and reducing diagnostic errors are essential in medical practice; OpenAI-o1, with advanced reasoning capabilities, performed better than GPT-4 on 15 Japanese National Medical Licensing Examination questions (accuracy: 100% vs 80%; contraindicated option detection: 87% vs 73%), though findings are preliminary due to the small sample size.…”
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