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Justin M. Johnson, Taghi M. Khoshgoftaar • Journal Of Big Data
(2019)
The purpose of this study is to examine existing deep learning techniques for addressing class imbalanced data. Effective classification with imbalanced data is an important area of research, as high class imbalance is naturally inherent in...
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DOI: https://doi.org/10.1186/s40537-019-0192-5
Shiyao Duan, Jiaojiao Li, Rui Song, Yunsong Li et al. • Remote Sensing
(2023)
Deep learning networks based on CNNs or transformers have made progress in spectral reconstruction (SR). However, many methods focus solely on feature extraction, overlooking the interpretability of network design. Additionally, models excl...
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Open Access (DOAJ)
DOI: 10.3390/rs15102619
Elisabetta Doria • Agathón
(2022)
The research proposal reports the outcomes of a research track concerning the automation of the architectural census of technological elements in urban environments, aiming at the development of a monitoring and management system for the bu...
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Open Access (DOAJ)
DOI: 10.19229/2464-9309/12162022
Kalaivani Sundararajan, Damon L. Woodard • ACM Computing Surveys
(2018)
In the recent past, deep learning methods have demonstrated remarkable success for supervised learning tasks in multiple domains including computer vision, natural language processing, and speech processing. In this article, we investigate ...
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DOI: https://doi.org/10.1145/3190618
Daniele Ravì, Charence Wong, Fani Deligianni, Melissa Berthelot et al. • IEEE Journal of Biomedical and Health Informatics
(2016)
With a massive influx of multimodality data, the role of data analytics in health informatics has grown rapidly in the last decade. This has also prompted increasing interests in the generation of analytical, data driven models based on mac...
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DOI: https://doi.org/10.1109/jbhi.2016.2636665
Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn • BMC Medical Imaging
(2025)
Abstract Background and purpose Accurate segmentation of brain metastases on Magnetic Resonance Imaging (MRI) is tedious and time-consuming for radiologists that could be optimized with deep learning (DL). Previous studies assessed several ...
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Open Access (DOAJ)
DOI: 10.1186/s12880-025-01643-y
Hu Dong, Xin Tong, Gang Liu • Fractal and Fractional
(2026)
For high-intensity focused ultrasound (HIFU) thermal ablation to be safe and effective, real-time, high-precision monitoring of tissue coagulative necrosis is essential. However, decoding the ultra-long, non-stationary radio frequency (RF) ...
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Open Access (DOAJ)
DOI: 10.3390/fractalfract10090609
Esraa Khatab, Ahmed Onsy, Ahmed Abouelfarag • Sensors
(2022)
One of the primary tasks undertaken by autonomous vehicles (AVs) is object detection, which comes ahead of object tracking, trajectory estimation, and collision avoidance. Vulnerable road objects (e.g., pedestrians, cyclists, etc.) pose a g...
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Open Access (DOAJ)
DOI: 10.3390/s22041663
Gabriel de Sousa Meira, João Victor Ferreira Guedes, Edilson de Souza Bias • Drones
(2024)
The use of geotechnologies in the field of diagnostic engineering has become ever more present in the identification of pathological manifestations in buildings. The implementation of Unmanned Aerial Vehicles (UAVs) and embedded sensors has...
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Open Access (DOAJ)
DOI: 10.3390/drones8070341
Mohammed Javeed Zaki, Wagner Meira • Cambridge University Press eBooks
(2020)
The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business an...
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DOI: https://doi.org/10.1017/9781108564175
Jason Bell • Wiley eBooks
(2014)
Emotion recognition is an important research topic.Physiological signals seem to be an appropriate way for emotion recognition and specific sensors are required to collect these data.Therefore, laboratory sensors are commonly used while the...
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DOI: https://doi.org/10.1002/9781119183464
Vishal Kumar Goar, Nagendra Singh Yadav • Advances in business information systems and analytics book series
(2024)
This chapter focuses on providing a complete grasp of the foundations of machine learning (ML). Machine learning is a rapidly evolving domain with wide-ranging applications, from natural language processing to autonomous vehicles. This chap...
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DOI: https://doi.org/10.4018/979-8-3693-1598-9.ch002
Luigi Capogrosso, Federico Cunico, Dong Seon Cheng, Franco Fummi et al. • IEEE Access
(2024)
The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware devices and their learning-based software architectures. T...
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DOI: https://doi.org/10.1109/access.2024.3365349
Ayushi Chahal, Preeti Gulia • International Journal of Innovative Technology and Exploring Engineering
(2019)
Now-a-days artificial intelligence has become an asset for engineering and experimental studies, just like statistics and calculus. Data science is a growing field for researchers and artificial intelligence, machine learning and deep learn...
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DOI: https://doi.org/10.35940/ijitee.l3550.1081219
José Padarian, Budiman Minasny, Alex B. McBratney • SOIL
(2020)
Abstract. The application of machine learning (ML) techniques in various fields of science has increased rapidly, especially in the last ten years. The increasing availability of soil data that can be efficiently acquired remotely and proxi...
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DOI: https://doi.org/10.5194/soil-6-35-2020
Andreas Müller, Sarah Guido (2016)
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teac...
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Vidya Baiju, Akshitha J, Namasiyava Naveen S • European Medical Journal
(2024)
Brain tumours are caused by the abnormal growth of cells in the brain. This occurs mainly due to genetic changes or exposure to X-ray radiation. When the tumours are detected early, they can be removed via surgery. The tumour can be removed...
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Open Access (DOAJ)
DOI: 10.33590/emj/NUUC2196
Drew Conway, J.M. White • CERN Document Server (European Organization for Nuclear Research)
(2012)
If you're an experienced programmer interested in crunching data, this book will get you started with machine learning-a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John...
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Ayaz Ahmad, Fawad Ahmad, Muhammad Suleman Khan, Adel Aldalbahi • PeerJ Computer Science
(2026)
Proactive caching in multi-tier cellular networks (MTCNs) is an efficient technique for alleviating heavy data traffic on backhaul links, thereby reducing content latency and increasing the overall cache hit ratio (CHR) and user satisfactio...
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Open Access (DOAJ)
DOI: 10.7717/peerj-cs.4004
S. Vijayan, Chiranji Lal Chowdhary • Scientific Reports
(2025)
Abstract The agricultural industry significantly relies on autonomous systems for detecting and analyzing rice diseases to minimize financial and resource losses, reduce yield reductions, improve processing efficiency, and ensure healthy cr...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-92646-w