# | Title | Journal | Year | Citations |
---|
1 | Extreme learning machine: Theory and applications | Neurocomputing | 2006 | 10,570 |
2 | Time series forecasting using a hybrid ARIMA and neural network model | Neurocomputing | 2003 | 2,840 |
3 | A survey of deep neural network architectures and their applications | Neurocomputing | 2017 | 2,242 |
4 | Deep learning for visual understanding: A review | Neurocomputing | 2016 | 1,644 |
5 | The self-organizing map | Neurocomputing | 1998 | 1,490 |
6 | Deep visual domain adaptation: A survey | Neurocomputing | 2018 | 1,255 |
7 | Financial time series forecasting using support vector machines | Neurocomputing | 2003 | 1,242 |
8 | Feature selection in machine learning: A new perspective | Neurocomputing | 2018 | 1,194 |
9 | GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classification | Neurocomputing | 2018 | 1,083 |
10 | Weighted least squares support vector machines: robustness and sparse approximation | Neurocomputing | 2002 | 1,072 |
11 | Binary grey wolf optimization approaches for feature selection | Neurocomputing | 2016 | 1,026 |
12 | On hyperparameter optimization of machine learning algorithms: Theory and practice | Neurocomputing | 2020 | 1,016 |
13 | Convex incremental extreme learning machine | Neurocomputing | 2007 | 1,012 |
14 | A review on the attention mechanism of deep learning | Neurocomputing | 2021 | 963 |
15 | Hybrid Whale Optimization Algorithm with simulated annealing for feature selection | Neurocomputing | 2017 | 884 |
16 | Learning and generalization characteristics of the random vector functional-link net | Neurocomputing | 1994 | 878 |
17 | A recurrent neural network based health indicator for remaining useful life prediction of bearings | Neurocomputing | 2017 | 848 |
18 | Designing a neural network for forecasting financial and economic time series | Neurocomputing | 1996 | 843 |
19 | Enhanced random search based incremental extreme learning machine | Neurocomputing | 2008 | 809 |
20 | Optimization method based extreme learning machine for classification | Neurocomputing | 2010 | 799 |
21 | A comprehensive survey on support vector machine classification: Applications, challenges and trends | Neurocomputing | 2020 | 795 |
22 | A review of clustering techniques and developments | Neurocomputing | 2017 | 766 |
23 | Error-backpropagation in temporally encoded networks of spiking neurons | Neurocomputing | 2002 | 764 |
24 | Artificial neural networks in hardware: A survey of two decades of progress | Neurocomputing | 2010 | 745 |
25 | Weighted extreme learning machine for imbalance learning | Neurocomputing | 2013 | 743 |
26 | A survey on fall detection: Principles and approaches | Neurocomputing | 2013 | 715 |
27 | A survey on security control and attack detection for industrial cyber-physical systems | Neurocomputing | 2018 | 694 |
28 | Recent advances and trends in visual tracking: A review | Neurocomputing | 2011 | 685 |
29 | Mean Absolute Percentage Error for regression models | Neurocomputing | 2016 | 684 |
30 | Blind separation of convolved mixtures in the frequency domain | Neurocomputing | 1998 | 673 |
31 | Bidirectional LSTM with attention mechanism and convolutional layer for text classification | Neurocomputing | 2019 | 650 |
32 | Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests (tsfresh – A Python package) | Neurocomputing | 2018 | 649 |
33 | Identification of rice diseases using deep convolutional neural networks | Neurocomputing | 2017 | 636 |
34 | Machine learning on big data: Opportunities and challenges | Neurocomputing | 2017 | 631 |
35 | The support vector machine under test | Neurocomputing | 2003 | 620 |
36 | Unsupervised real-time anomaly detection for streaming data | Neurocomputing | 2017 | 601 |
37 | Remaining useful life estimation of engineered systems using vanilla LSTM neural networks | Neurocomputing | 2018 | 560 |
38 | Emotional state classification from EEG data using machine learning approach | Neurocomputing | 2014 | 559 |
39 | Auto-encoder based dimensionality reduction | Neurocomputing | 2016 | 559 |
40 | : Two-directional two-dimensional PCA for efficient face representation and recognition | Neurocomputing | 2005 | 545 |
41 | Time series forecasting of petroleum production using deep LSTM recurrent networks | Neurocomputing | 2019 | 535 |
42 | Recent advances in deep learning for object detection | Neurocomputing | 2020 | 534 |
43 | Evaluation of simple performance measures for tuning SVM hyperparameters | Neurocomputing | 2003 | 510 |
44 | An approach to blind source separation based on temporal structure of speech signals | Neurocomputing | 2001 | 502 |
45 | Transition-Aware Human Activity Recognition Using Smartphones | Neurocomputing | 2016 | 502 |
46 | Natural Actor-Critic | Neurocomputing | 2008 | 490 |
47 | A density-based method for adaptive LDA model selection | Neurocomputing | 2009 | 480 |
48 | A comparison of PCA, KPCA and ICA for dimensionality reduction in support vector machine | Neurocomputing | 2003 | 471 |
49 | Multilayer perceptrons for classification and regression | Neurocomputing | 1991 | 461 |
50 | Face detection using deep learning: An improved faster RCNN approach | Neurocomputing | 2018 | 459 |