Search Results - "Learning algorithms"

A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI by Tjoa, Erico, Guan, Cuntai

“…Recently, artificial intelligence and machine learning in general have demonstrated remarkable performances in many tasks, from image processing to natural…”
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Transfer Learning for Brain-Computer Interfaces: A Euclidean Space Data Alignment Approach by He, He, Wu, Dongrui

“…Objective: This paper targets a major challenge in developing practical electroencephalogram (EEG)-based brain-computer interfaces (BCIs): how to cope with…”
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Competition-level code generation with AlphaCode by Li, Yujia, Choi, David, Chung, Junyoung, Kushman, Nate, Schrittwieser, Julian, Leblond, Rémi, Eccles, Tom, Keeling, James, Gimeno, Felix, Dal Lago, Agustin, Hubert, Thomas, Choy, Peter, de Masson d'Autume, Cyprien, Babuschkin, Igor, Chen, Xinyun, Huang, Po-Sen, Welbl, Johannes, Gowal, Sven, Cherepanov, Alexey, Molloy, James, Mankowitz, Daniel J, Sutherland Robson, Esme, Kohli, Pushmeet, de Freitas, Nando, Kavukcuoglu, Koray, Vinyals, Oriol

“…Programming is a powerful and ubiquitous problem-solving tool. Systems that can assist programmers or even generate programs themselves could make programming…”
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Dendritic Neuron Model With Effective Learning Algorithms for Classification, Approximation, and Prediction by Gao, Shangce, Zhou, Mengchu, Wang, Yirui, Cheng, Jiujun, Yachi, Hanaki, Wang, Jiahai

“…An artificial neural network (ANN) that mimics the information processing mechanisms and procedures of neurons in human brains has achieved a great success in…”
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Predicting property prices with machine learning algorithms by Ho, Winky K.O., Tang, Bo-Sin, Wong, Siu Wai

“…This study uses three machine learning algorithms including, support vector machine (SVM), random forest (RF) and gradient boosting machine (GBM) in the…”
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Emerging Wearable Interfaces and Algorithms for Hand Gesture Recognition: A Survey by Jiang, Shuo, Kang, Peiqi, Song, Xinyu, Lo, Benny, Shull, Peter

“…Hands are vital in a wide range of fundamental daily activities, and neurological diseases that impede hand function can significantly affect quality of life…”
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Optimal performance of simple low-cost optical physical unclonable functions resilient to machine learning attacks by Akriotou, Marialena, Bartsokas, Theodoros, Veinidis, Christos, Syvridis, Dimitris

“…In this paper we reconsider Physical Unclonable Functions based on the traditional approach of optical scattering to randomly disordered optical media. These…”
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Predicting the impacts of land use/land cover changes on seasonal urban thermal characteristics using machine learning algorithms by Kafy, Abdulla - Al, Saha, Milan, Faisal, Abdullah-Al, Rahaman, Zullyadini A., Rahman, Muhammad Tauhidur, Liu, Desheng, Fattah, Md. Abdul, Al Rakib, Abdullah, AlDousari, Ahmad E., Rahaman, Sk Nafiz, Hasan, Md Zakaria, Ahasan, Md Ahasanul Karim

“…Changes in land use/land cover (LULC) and land surface temperatures (LST) contribute significantly to the formation and intensity of urban heat islands (UHI)…”
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Machine learning ‐ Basic principles by Bernardes, Rui

“…Machine learning, a subcategory of AI, is a method of data analysis. It allows computers to learn from data and build models from which predictions can be…”
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Artificial Intelligence in Cardiology: Present and Future by Lopez-Jimenez, Francisco, Attia, Zachi, Arruda-Olson, Adelaide M., Carter, Rickey, Chareonthaitawee, Panithaya, Jouni, Hayan, Kapa, Suraj, Lerman, Amir, Luong, Christina, Medina-Inojosa, Jose R., Noseworthy, Peter A., Pellikka, Patricia A., Redfield, Margaret M., Roger, Veronique L., Sandhu, Gurpreet S., Senecal, Conor, Friedman, Paul A.

“…Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of various types but most often to deep neural networks…”
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Broad Learning System Based on Maximum Correntropy Criterion by Zheng, Yunfei, Chen, Badong, Wang, Shiyuan, Wang, Weiqun

“…As an effective and efficient discriminative learning method, broad learning system (BLS) has received increasing attention due to its outstanding performance…”
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TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods by Collins, Gary S, Moons, Karel G M, Dhiman, Paula, Riley, Richard D, Beam, Andrew L, Van Calster, Ben, Ghassemi, Marzyeh, Liu, Xiaoxuan, Reitsma, Johannes B, van Smeden, Maarten, Boulesteix, Anne-Laure, Camaradou, Jennifer Catherine, Celi, Leo Anthony, Denaxas, Spiros, Denniston, Alastair K, Glocker, Ben, Golub, Robert M, Harvey, Hugh, Heinze, Georg, Hoffman, Michael M, Kengne, André Pascal, Lam, Emily, Lee, Naomi, Loder, Elizabeth W, Maier-Hein, Lena, Mateen, Bilal A, McCradden, Melissa D, Oakden-Rayner, Lauren, Ordish, Johan, Parnell, Richard, Rose, Sherri, Singh, Karandeep, Wynants, Laure, Logullo, Patricia

“…The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) statement was published in 2015 to provide the…”
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Machine learning-aided real-time detection of keyhole pore generation in laser powder bed fusion by Ren, Zhongshu, Gao, Lin, Clark, Samuel J, Fezzaa, Kamel, Shevchenko, Pavel, Choi, Ann, Everhart, Wes, Rollett, Anthony D, Chen, Lianyi, Sun, Tao

“…Porosity defects are currently a major factor that hinders the widespread adoption of laser-based metal additive manufacturing technologies. One common…”
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Performance Comparison of an LSTM-based Deep Learning Model versus Conventional Machine Learning Algorithms for Streamflow Forecasting by Rahimzad, Maryam, Moghaddam Nia, Alireza, Zolfonoon, Hosam, Soltani, Jaber, Danandeh Mehr, Ali, Kwon, Hyun-Han

“…Streamflow forecasting plays a key role in improvement of water resource allocation, management and planning, flood warning and forecasting, and mitigation of…”
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Multi-step ahead forecasting of heat load in district heating systems using machine learning algorithms by Xue, Puning, Jiang, Yi, Zhou, Zhigang, Chen, Xin, Fang, Xiumu, Liu, Jing

“…Predicting next-day heat load curves is essential to guarantee sufficient heat supply and optimal operation of district heat systems (DHSs). Existing studies…”
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A Survey on Self-Supervised Learning: Algorithms, Applications, and Future Trends by Gui, Jie, Chen, Tuo, Zhang, Jing, Cao, Qiong, Sun, Zhenan, Luo, Hao, Tao, Dacheng

“…Deep supervised learning algorithms typically require a large volume of labeled data to achieve satisfactory performance. However, the process of collecting…”
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Beyond bias and discrimination: redefining the AI ethics principle of fairness in healthcare machine-learning algorithms by Giovanola, Benedetta, Tiribelli, Simona

“…The increasing implementation of and reliance on machine-learning (ML) algorithms to perform tasks, deliver services and make decisions in health and…”
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Empirical comparison and analysis of web-based cell-penetrating peptide prediction tools by Su, Ran, Hu, Jie, Zou, Quan, Manavalan, Balachandran, Wei, Leyi

“…Abstract Cell-penetrating peptides (CPPs) facilitate the delivery of therapeutically relevant molecules, including DNA, proteins and oligonucleotides, into…”
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Real-Time Hyperbola Recognition and Fitting in GPR Data by Qingxu Dou, Lijun Wei, Magee, Derek R., Cohn, Anthony G.

“…The problem of automatically recognizing and fitting hyperbolae from ground-penetrating radar (GPR) images is addressed, and a novel technique computationally…”
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Machine learning-enabled high-entropy alloy discovery by Rao, Ziyuan, Tung, Po-Yen, Xie, Ruiwen, Wei, Ye, Zhang, Hongbin, Ferrari, Alberto, Klaver, T P C, Körmann, Fritz, Sukumar, Prithiv Thoudden, Kwiatkowski da Silva, Alisson, Chen, Yao, Li, Zhiming, Ponge, Dirk, Neugebauer, Jörg, Gutfleisch, Oliver, Bauer, Stefan, Raabe, Dierk

“…High-entropy alloys are solid solutions of multiple principal elements that are capable of reaching composition and property regimes inaccessible for dilute…”
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