Multimodal genetic algorithms-based algorithm for automatic point correspondence

Delibasis, Konstantinos K.; Asvestas, Pantelis A.; Matsopoulos, George K.

doi:10.1016/j.patcog.2010.06.009

Cited by 9 publications

(4 citation statements)

References 48 publications

(57 reference statements)

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“…SentiWordNet is the most widely used lexicon in the field of sentiment analysis [ 19 , 40 ]. However, due to the different senses of words, this approach may not obtain a good result in some domains.…”

Section: Literature Of Opinion Miningmentioning

confidence: 99%

“…Vocabulary based approaches suffer from a lack of vocabulary, on the other hand, machine learning approaches usually show lower accuracy than vocabulary based approaches. Iqbal and his team [19] presented an integrated framework that bridges the gaps between vocabulary-machine learning approaches for achieving accuracy and scalability. To solve the scalability problem created by increasing the set features, a new genetic algorithm (GA) is suggested using a feature reduction method.…”

Section: Literature Of Opinion Miningmentioning

confidence: 99%

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Deterministic solution of algebraic equations in sentiment analysis

Zahedi

Basiri

2023

Multimed Tools Appl

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Text mining methods usually use statistical information to solve text and language-independent procedures. Text mining methods such as polarity detection based on stochastic patterns and rules need many samples to train. On the other hand, deterministic and non-probabilistic methods are easy to solve and faster than other methods but are not efficient in NLP data. In this article, a fast and efficient deterministic method for solving the problems is proposed. In the proposed method firstly we transform text and labels into a set of equations. In the second step, a mathematical solution of ill-posed equations known as Tikhonov regularization was used as a deterministic and non-probabilistic way including additional assumptions, such as smoothness of solution to assign a weight that can reflect the semantic information of each sentimental word. We confirmed the efficiency of the proposed method in the SemEval-2013 competition, ESWC Database and Taboada database as three different cases. We observed improvement of our method over negative polarity due to our proposed mathematical step. Moreover, we demonstrated the effectiveness of our proposed method over the most common and traditional machine learning, stochastic and fuzzy methods.

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Section: Literature Of Opinion Miningmentioning

confidence: 99%

Section: Literature Of Opinion Miningmentioning

confidence: 99%

Deterministic solution of algebraic equations in sentiment analysis

Zahedi

Basiri

2023

Multimed Tools Appl

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“…Automatic point determination: The problem of automatic determination of point correspondence between two images can be formulated as a MMO problem. A genetic algorithm using niching techniques was used to determine the automatic point correspondence between two images [157]. The niching GA method was able to discover optimal solutions that are measured by the similarity between patches of two images.…”

Section: Examples Of Real-world Applicationsmentioning

confidence: 99%

Seeking Multiple Solutions: An Updated Survey on Niching Methods and Their Applications

Epitropakis

Deb

et al. 2017

IEEE Trans. Evol. Computat.

252

101

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Abstract-Multi-modal optimization (MMO) aiming to locate multiple optimal (or near-optimal) solutions in a single simulation is an important topic which has practical relevance in problem solving across many fields. Population-based meta-heuristics have been shown particularly effective in solving MMO prolems, if equipped with specifically-designed diversity-preserving mechanisms, commonly known as niching methods. This paper provides an updated survey on niching methods. The paper first revisits the fundamental concepts about niching and its most representative schemes, then reviews the more recent development of niching methods, including novel and hybrid methods, performance measures, and benchmarks for their assessment. Furthermore, the paper surveys previous attempts on leveraging the capabilities of niching to facilitate various optimization (e.g., multi-objective and dynamic optimization) and machine learning (e.g., clustering, feature selection, and learning ensembles) tasks. A list of successful applications of niching methods to real-world problems is provided to demonstrate that niching methods are able to provide solutions that are difficult for conventional optimization methods to offer. The significant practical value of niching methods is clearly exemplified through these applications. Finally, the paper poses challenges and research questions on niching that are yet to be appropriately addressed. Providing answers to these questions is crucial before we can bring more fruitful benefits of niching to real-world problem solving.

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“…Otherwise the difference will not be found accurately. Researchers have developed many alignment algorithms in recent years, which can be divided into different classes: iterative closest point (ICP) [4][5][6] and robust point matching (RPM) [7,8]. The ICP algorithm is proposed by Besl and Mckay [4] on the basis of quaternions and singular value decomposition (SVD), which effectively solves the point alignment problem.…”

Section: Introductionmentioning

confidence: 99%

A hybrid point cloud alignment method combining particle swarm optimization and iterative closest point method

Wang

2014

Adv. Manuf.

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3D quality inspection is widely applied in many industrial fields including mould design, automotive and blade manufacturing, etc. A commonly used method is to obtain the point cloud of the inspected object and make a comparison between the point cloud and the corresponding CAD model or template. Thus, it is important to align the point cloud with the template first and foremost. Moreover, for the purpose of automatization of quality inspection, this alignment process is expected to be completed without manual interference. In this paper, we propose to combine the particle swarm optimization (PSO) with iterative closest point (ICP) algorithm to achieve the automated point cloud alignment. The combination of the two algorithms can achieve a balance between the alignment speed and accuracy, and avoid the local optimal caused by bad initial position of the point cloud.

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Multimodal genetic algorithms-based algorithm for automatic point correspondence

Cited by 9 publications

References 48 publications

Deterministic solution of algebraic equations in sentiment analysis

Deterministic solution of algebraic equations in sentiment analysis

Seeking Multiple Solutions: An Updated Survey on Niching Methods and Their Applications

A hybrid point cloud alignment method combining particle swarm optimization and iterative closest point method

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