Institution
Griffith University
Education•Brisbane, Queensland, Australia•
About: Griffith University is a education organization based out in Brisbane, Queensland, Australia. It is known for research contribution in the topics: Population & Context (language use). The organization has 13830 authors who have published 49318 publications receiving 1420865 citations.
Topics: Population, Context (language use), Poison control, Health care, Tourism
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the authors present an analysis of the nature and possible cognitive consequences of situated learning and their sources, as well as an account of the likely cognitive consequences and their likely sources.
343 citations
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TL;DR: Alarming losses comprising one-tenth (3.3 million km2) of global wilderness areas over the last two decades are demonstrated, particularly in the Amazon and central Africa, and an immediate need for international policies to recognize the vital values of wilderness and the unprecedented threats they face is underscore.
342 citations
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TL;DR: In this article, the authors provide an overview of various convolutional neural network (CNN) models and provide several rules of thumb for functions and hyperparameter selection, as well as open issues and promising directions for future work.
Abstract: A convolutional neural network (CNN) is one of the most significant networks in the deep learning field. Since CNN made impressive achievements in many areas, including but not limited to computer vision and natural language processing, it attracted much attention from both industry and academia in the past few years. The existing reviews mainly focus on CNN's applications in different scenarios without considering CNN from a general perspective, and some novel ideas proposed recently are not covered. In this review, we aim to provide some novel ideas and prospects in this fast-growing field. Besides, not only 2-D convolution but also 1-D and multidimensional ones are involved. First, this review introduces the history of CNN. Second, we provide an overview of various convolutions. Third, some classic and advanced CNN models are introduced; especially those key points making them reach state-of-the-art results. Fourth, through experimental analysis, we draw some conclusions and provide several rules of thumb for functions and hyperparameter selection. Fifth, the applications of 1-D, 2-D, and multidimensional convolution are covered. Finally, some open issues and promising directions for CNN are discussed as guidelines for future work.
342 citations
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TL;DR: A critical analysis of the strengths and weaknesses of the NbS principles can inform the review and revision of principles supporting specific types of N bS (such as the approaches reviewed here), as well as serve as the foundation for the development of standards for the successful implementation of NBS.
341 citations
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TL;DR: The comprehensive results and various comparisons reveal that the EPD has a remarkable impact on the efficacy of the GOA and using the selection mechanism enhanced the capability of the proposed approach to outperform other optimizers and find the best solutions with improved convergence trends.
Abstract: Searching for the optimal subset of features is known as a challenging problem in feature selection process. To deal with the difficulties involved in this problem, a robust and reliable optimization algorithm is required. In this paper, Grasshopper Optimization Algorithm (GOA) is employed as a search strategy to design a wrapper-based feature selection method. The GOA is a recent population-based metaheuristic that mimics the swarming behaviors of grasshoppers. In this work, an efficient optimizer based on the simultaneous use of the GOA, selection operators, and Evolutionary Population Dynamics (EPD) is proposed in the form of four different strategies to mitigate the immature convergence and stagnation drawbacks of the conventional GOA. In the first two approaches, one of the top three agents and a randomly generated one are selected to reposition a solution from the worst half of the population. In the third and fourth approaches, to give a chance to the low fitness solutions in reforming the population, Roulette Wheel Selection (RWS) and Tournament Selection (TS) are utilized to select the guiding agent from the first half. The proposed GOA_EPD approaches are employed to tackle various feature selection tasks. The proposed approaches are benchmarked on 22 UCI datasets. The comprehensive results and various comparisons reveal that the EPD has a remarkable impact on the efficacy of the GOA and using the selection mechanism enhanced the capability of the proposed approach to outperform other optimizers and find the best solutions with improved convergence trends. Furthermore, the comparative experiments demonstrate the superiority of the proposed approaches when compared to other similar methods in the literature.
341 citations
Authors
Showing all 14162 results
Name | H-index | Papers | Citations |
---|---|---|---|
Rasmus Nielsen | 135 | 556 | 84898 |
Claudiu T. Supuran | 134 | 1973 | 86850 |
Jeffrey D. Sachs | 130 | 692 | 86589 |
David Smith | 129 | 2184 | 100917 |
Michael R. Green | 126 | 537 | 57447 |
John J. McGrath | 120 | 791 | 124804 |
E. K. U. Gross | 119 | 1154 | 75970 |
David M. Evans | 116 | 632 | 74420 |
Mike Clarke | 113 | 1037 | 164328 |
Wayne Hall | 111 | 1260 | 75606 |
Patrick J. McGrath | 107 | 681 | 51940 |
Peter K. Smith | 107 | 855 | 49174 |
Erko Stackebrandt | 106 | 633 | 68201 |
Phyllis Butow | 102 | 731 | 37752 |
John Quackenbush | 99 | 427 | 67029 |