Search Results - (( sequence evaluation method algorithm ) OR ( leaf optimization method algorithm ))
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1
Application of genetic algorithm methods to optimize flowshop sequencing problem
Published 2008“…This project will define the application of genetic algorithm method in solving flow shop sequencing problem in details and evaluate the strength and weakness of genetic algorithm method in order to optimize the optimization problem. …”
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Undergraduates Project Papers -
2
Comparison and evaluation of multiple sequence alignment tools in bininformatics
Published 2009“…This study addresses this critical issue in relation to MSA algorithms by systematically comparing and evaluating the functionality, usability and the algorithms of three famous multiple sequence alignment tools. …”
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Article -
3
Automated plant classification system using a hybrid of shape and color features of the leaf
Published 2016“…Automated plant leaf classification is a computerized approach that employs computer vision and machine learning algorithms to identify a plant based on the features of its leaf. …”
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4
Leaf condition analysis using convolutional neural network and vision transformer
Published 2024“…Besides, existing leaf disease detection programs do not provide an optimized user’s experience. …”
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5
Plant leaf recognition algorithm using ant colony-based feature extraction technique
Published 2013“…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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6
Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences
Published 2021“…This paper also introduces a detailed survey of the different initialization methods of PSO and DE based on quasi-random sequence families such as the Sobol sequence, Halton sequence, and uniform random distribution. …”
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Article -
7
Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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8
Spectral texture segmentation of Magnetic Resonance Imaging (MRI) brain images for glioma brain tumour detection / Rosniza Roslan
Published 2013“…A new double thresholding algorithm and a fully automated multiple seed points selection algorithm that works on all three MRI image sequences are also proposed. …”
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9
Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…In order to develop the proposed methods, the baseline techniques are studied to develop the proposed algorithms. …”
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Book Chapter -
10
A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…Existing SKF methods are then compared to the findings of the DSKFO algorithm. …”
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11
The normalized random map of gradient for generating multifocus image fusion
Published 2020“…It successes to eliminate the mathematical and algorithm problems. Furthermore, the evaluation of proposed method based on the fused image quality. …”
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Article -
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Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga
Published 2022“…First, to investigate the methods used to address limitations associated with microbiome-based datasets in colorectal cancer identification using deep neural network algorithms. …”
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13
Blotch removal using multi-level scanning, shape analysis, and meta heuristic techniques
Published 2015“…The algorithms were applied to two real image sequences which were contaminated to unknown blotches and the results were extracted for evaluation of proposed methods. …”
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14
Deep plant: A deep learning approach for plant classification / Lee Sue Han
Published 2018“…They look for the procedures or algorithms that maximize the use of leaf databases for plant predictive modelling, but this results in leaf features which are liable to change with different leaf data and feature extraction techniques. …”
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15
Kalman filter based impedance parameter estimation for transmission line and distribution line
Published 2019“…Therefore, a detailed study on developing and evaluating the new algorithms for transmission line parameter estimation is considered in this thesis. …”
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16
Depth frame loss concealment for wireless transmission utilising motion detection information
Published 2014“…The proposed method is able to improve the quality of video in comparison with frame copy algorithm. …”
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17
Filtering of Background DNA Sequences Improves DNA Motif Prediction Using Clustering Techniques
Published 2013“…Our method is motivated by the evolutionary conservation property of binding sites as opposed to randomness of background sequences. …”
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Article -
18
Multilevel optimization for dense motion estimation
Published 2011“…Experimental results on three image sequences using four models of optical flow with different computational efforts show that the FMG/Opt algorithm outperforms significantly both the TN and MR/Opt algorithms in terms of the computational work and the quality of the optical flow estimation.…”
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Monograph -
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Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm
Published 2019“…On the other hand, the recent ASP research tends to explore the potential of a relatively new algorithm to optimise ASP. Therefore, the aim of this research is to establish a methodology and implement the relatively new algorithm to optimise the Energy Efficient Assembly Sequence Planning (EE-ASP) problem. …”
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20
Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…An example of the DNN model is the Attentive Sequence-to-Sequence (Seq2Seq) model that was first created to tackle a problem setting in language processing. …”
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