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Refinado por: Base de dados/Biblioteca: Gale Academic OneFile remover
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11
Classification of working memory loads using hybrid EEG and fNIRS in machine learning paradigm
Classification of working memory loads using hybrid EEG and fNIRS in machine learning paradigm
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Classification of working memory loads using hybrid EEG and fNIRS in machine learning paradigm

Mandal, S ; Singh, B.K ; Thakur, K

Electronics letters, 2020-12, Vol.56 (25), p.1386-1389 [Periódico revisado por pares]

The Institution of Engineering and Technology

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12
Classification of fruits using computer vision and a multiclass support vector machine
Classification of fruits using computer vision and a multiclass support vector machine
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Classification of fruits using computer vision and a multiclass support vector machine

Zhang, Yudong ; Wu, Lenan

Sensors (Basel, Switzerland), 2012-09, Vol.12 (9), p.12489-12505 [Periódico revisado por pares]

Switzerland: MDPI AG

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13
Mapping of Post-Wildfire Burned Area Using a Hybrid Algorithm and Satellite Data: The Case of the Camp Fire Wildfire in California, USA
Mapping of Post-Wildfire Burned Area Using a Hybrid Algorithm and Satellite Data: The Case of the Camp Fire Wildfire in California, USA
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Mapping of Post-Wildfire Burned Area Using a Hybrid Algorithm and Satellite Data: The Case of the Camp Fire Wildfire in California, USA

Syifa, Mutiara ; Panahi, Mahdi ; Lee, Chang-Wook

Remote sensing (Basel, Switzerland), 2020-02, Vol.12 (4), p.623 [Periódico revisado por pares]

MDPI AG

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14
A Machine Learning Approach to Classify Biomedical Acoustic Features for Baby Cries
A Machine Learning Approach to Classify Biomedical Acoustic Features for Baby Cries
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A Machine Learning Approach to Classify Biomedical Acoustic Features for Baby Cries

Aggarwal, Gaurav ; Jhajharia, Kavita ; Izhar, Jaweria ; Kumar, Manoj ; Abualigah, Laith

Journal of voice, 2023-07 [Periódico revisado por pares]

United States: Elsevier Inc

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15
Linear and non-linear SVM prediction for fresh properties and compressive strength of high volume fly ash self-compacting concrete
Linear and non-linear SVM prediction for fresh properties and compressive strength of high volume fly ash self-compacting concrete
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Linear and non-linear SVM prediction for fresh properties and compressive strength of high volume fly ash self-compacting concrete

Azimi-Pour, Mohammad ; Eskandari-Naddaf, Hamid ; Pakzad, Amir

Construction & building materials, 2020-01, Vol.230, p.117021, Article 117021 [Periódico revisado por pares]

Elsevier Ltd

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16
Non-linear LS-SVM with RBF-kernel-based approach for AGC of multi-area energy systems
Non-linear LS-SVM with RBF-kernel-based approach for AGC of multi-area energy systems
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Non-linear LS-SVM with RBF-kernel-based approach for AGC of multi-area energy systems

Sharma, Gulshan ; Panwar, Akhilesh ; Nasiruddin, Ibraheem ; Bansal, Ramesh C

IET generation, transmission & distribution, 2018-08, Vol.12 (14), p.3510-3517 [Periódico revisado por pares]

The Institution of Engineering and Technology

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17
Identification of Green, Oolong and Black Teas in China via Wavelet Packet Entropy and Fuzzy Support Vector Machine
Identification of Green, Oolong and Black Teas in China via Wavelet Packet Entropy and Fuzzy Support Vector Machine
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Identification of Green, Oolong and Black Teas in China via Wavelet Packet Entropy and Fuzzy Support Vector Machine

Wang, Shuihua ; Yang, Xiaojun ; Zhang, Yudong ; Phillips, Preetha ; Yang, Jianfei ; Yuan, Ti-Fei

Entropy (Basel, Switzerland), 2015-10, Vol.17 (10), p.6663-6682 [Periódico revisado por pares]

Basel: MDPI AG

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18
Topological Properties of Resting-State fMRI Functional Networks Improve Machine Learning-Based Autism Classification
Topological Properties of Resting-State fMRI Functional Networks Improve Machine Learning-Based Autism Classification
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Topological Properties of Resting-State fMRI Functional Networks Improve Machine Learning-Based Autism Classification

Kazeminejad, Amirali ; Sotero, Roberto C

Frontiers in neuroscience, 2019-01, Vol.12, p.1018-1018 [Periódico revisado por pares]

Switzerland: Frontiers Research Foundation

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19
Combination of Support Vector Machine and K-Fold cross validation to predict compressive strength of concrete in marine environment
Combination of Support Vector Machine and K-Fold cross validation to predict compressive strength of concrete in marine environment
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Combination of Support Vector Machine and K-Fold cross validation to predict compressive strength of concrete in marine environment

Ling, Hao ; Qian, Chunxiang ; Kang, Wence ; Liang, Chengyao ; Chen, Huaicheng

Construction & building materials, 2019-05, Vol.206, p.355-363 [Periódico revisado por pares]

Elsevier Ltd

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20
SVM-based PQ disturbance recognition system
SVM-based PQ disturbance recognition system
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SVM-based PQ disturbance recognition system

Huang, Jiansheng ; Jiang, Zhuhan ; Rylands, Leanne ; Negnevitsky, Michael

IET generation, transmission & distribution, 2018-01, Vol.12 (2), p.328-334 [Periódico revisado por pares]

The Institution of Engineering and Technology

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