Search Results - (( model relation ((bees algorithm) OR (new algorithm)) ) OR ( image classification _ algorithm ))

An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

“…The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

“…Moreover, adding new classes or new food images features has no significant consequence on the model knowledge. …”
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An improved artificial bee colony algorithm based on mean best-guided approach for continuous optimization problems and real brain MRI images segmentation by Alrosan, Ayat, Alomoush, Waleed, Norwawi, Norita, Alswaitti, Mohammed, Makhadmeh, Sharif Naser

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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Sentiment analysis of restaurant reviews in Kuala Terengganu based on K-Nearest Neighbor/ Siti Syazwana Jafri by Jafri, Siti Syazwana

“…The chosen technique is classification and the algorithm that will be applied in the classification process is K- Nearest Neighbor (KNN). …”
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Image-based air quality estimation using convolutional neural network optimized by genetic algorithms: A multi-dataset approach by Khan, Arshad Ali, Mazlina, Abdul Majid, Dandoush, Abdulhalim

“…Traditional methods using fixed monitoring stations have challenges related to high costs and limited coverage. This paper proposes a new approach using convolutional neural networks with genetic algorithms for estimating air quality directly from images. …”
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Integration of object-based image analysis and data mining techniques for detailes urban mapping using remote sensing by Hamedianfar, Alireza

“…This algorithm represents the decision tree knowledge model, enables fast classification of intra-urban classes, and disables subjectivities related to the interaction with analysts. …”
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Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine by Fathi Mahdi Elsiddig Haroun, Mr.

“…In this dissertation, a new vegetation encroachment detection method was proposed by studying the feasibility of using the visible-light band of highresolution satellite images using the RetinaNet deep learning model and Support Vector Machine algorithm (SVM). …”

Visual codebook analysis in image understanding / Hoo Wai Lam by Hoo, Wai Lam

“…Therefore, a zero-shot learning approach is needed to classify those images that have not been seen by the classification model before. …”
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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Machine-learning guided fracture density seismic inversion: A new approach in fractured basement characterisation by Shamsuddin, A.A.S., Purnomo, E.W., Ghosh, D.P.

“…A machine learning algorithm of well log fracture density - borehole image log (BHI) guided seismic inversion was performed. …”
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Identifying the mechanism to forecast the progression of Alzheimer’s disease from mild cognitive impairment using deep learning by Hiu, Theresa Wei Xin

“…This study also implemented a CNN algorithm based on 3D ResNet-18 model using weights from ImageNet for the classification task of CN vs AD and sMCI vs pMCI. …”
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Time series forecasting of energy commodity using grey wolf optimizer by Yusof, Yuhanis, Mustaffa, Zuriani

“…The ability to model and perform decision making is an essential feature of many real-world applications including the forecasting of commodity prices.In this study, a forecasting model based on a relatively new Swarm Intelligence (SI) behaviour, namely Grey Wolf Optimizer (GWO), is developed for short term time series forecasting.The model is built upon data obtained from the West Texas Intermediate (WTI) crude oil and gasoline price.Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE).Results showed that the GWO model outperformed DE in both crude oil and gasoline price forecasting. …”
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Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway by Ahmad Muhaimin, Ismail, Muhammad Akmal, Remli, Yee Wen, Choon, Nurul Athirah, Nasarudin, Norsyahidatul Nazirah, Ismail, Mohd Arfian, Ismail, Mohd Saberi, Mohamad

“…Parameter estimation is a challenging task in the biological process due to the complexity and nonlinearity of the model. Therefore, we propose the Artificial Bee Colony algorithm (ABC) to estimate the parameters in the fermentation pathway of S. cerevisiae to obtain more accurate values. …”
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Time Series Forecasting of Energy Commodity using Grey Wolf Optimizer by Zuriani, Mustaffa, Yuhanis, Yusof

“…Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE). …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

“…Therefore, an improved feature extraction and selection for sky image classification (FESSIC) algorithm is proposed. …”
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Near-infrared technique for oil palm fruit grading system by Saeed, Osama Mohamed Ben

“…The strategic positioning of the halogen and applied security design (ASD) lamps helps provide a shadow for free illumination. Image processing approaches, such as image acquisition, image pre-processing, and image feature extraction, as well as image classification were developed to automate the ripeness grading for oil palm fruit bunches. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…In addition, the best band selected for image classification is not necessarily the best for classification.A Best Band Selection Index (BBSI) algorithm was developed which is capable of selecting the best band combination for image visualization and supervised classification. …”
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Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza by Khaimuza, Haris Hidayatullah

“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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