Search Results - (( learning segmentation learning algorithm ) OR ( evolution optimization path algorithm ))

The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

“…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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Development of an improved GWO algorithm for solving optimal paths in complex vertical farms with multi-robot multi-tasking by Shen, Jiazheng, Hong, Tang Sai, Fan, Luxin, Zhao, Ruixin, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan

“…The EPDE-GWO algorithm is compared with Genetic Algorithm (GA), Simulated Annealing (SA), Dung Beetle Optimizer (DBO), and Particle Swarm Optimization (PSO). …”
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

“…This study aims to develop an algorithm for the AOI system to segment and detect surface defects, requiring low processing power and a small number of learning dataset with labelling error resistance. …”
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Path optimization using genetic algorithm evolution by Low C.Y., Chong K.H., Salleh K., Johnny K.S.P.

Object based segmentation and analysis using deep learning algorithm for cats and dogs images by N.Rajandhiran, Shreevishal

“…User intervention is constantly required to perform the segmentation. In addition, the algorithms used for the segmentation are conventional rather than modern deep learning techniques which is inevitably more efficient. …”
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Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim by Hashim, Siti Zuraifah

“…Roadways and telephone systems are the examples of them. Genetic Algorithms (GA), pioneered by John Holland, applies the principle of evolution found in nature to the problem of finding an optimal solution. …”
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Brain tumor image segmentation using deep learning approach by Darshan, Suresh

“…Deep learning algorithm is able to provide good tumor segmentation results compared to other conventional segmentation algorithms as it learns from the labeled brain MRIs to predict the location of tumor region and consequently segment the tumor. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

“…This survey reviewed 22 machine learning and 88 deep learning-based segmentation of prostate MRI papers, including all MRI modalities. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

“…This survey reviewed 22 machine learning and 88 deep learning-based segmentation of prostate MRI papers, including all MRI modalities. …”
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Differential evolution optimization for constrained routing in Wireless Mesh Networks by Sanni, Mistura Laide, Hassan Abdalla Hashim, Aisha, Hassan, Wan Haslina, Ahmed, Gharib Subhi Mahmoud, Anwar, Farhat, Zakaria, Omar

“…This solution addresses efficient and optimal routing path construction for cost and quality metrics of the application. …”
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A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…We propose a new reinforced active learning strategy based on a deep reinforcement learning algorithm. …”
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Integration of image processing algorithm and deep learning approaches to monitor ginger plant by Tan, Cheng Yong

“…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. …”
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A Reinforcement Learning Algorithm for object segmentation in complex images by Usmani, Usman Ahmad

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Integration of image processing algorithm and deep learning approaches to monitor ginger plant by Tan, Cheng Yong

“…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. …”
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Deep Learning Based image segmentation for expensive soil desiccation crack recognition and qualification by Ling, Hui Yean

“…This study investigated the feasibility and effectiveness of image-based techniques using advanced deep learning algorithms to quantify desiccation cracks in expansive soils. …”
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Automated visual defect detection using deep learning by Loh, Xiao

“…The main goal of this project is to study and develop various automated defect detection models by utilizing state-of-the-art deep learning segmentation algorithms, including U-Net, Double U-Net, SETR, TransU-Net, TransDAU-Net, CAM and SEAM to perform semantic segmentation in fully supervised and weakly supervised learning manners. …”
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A novel deep learning instance segmentation model for automated marine oil spill detection by Temitope Yekeen, S., Balogun, A.L., Wan Yusof, K.B.

“…The study concluded that the deep learning instance segmentation model performs better than conventional machine learning models and deep learning semantic segmentation models in detection and segmentation. …”
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A novel deep learning instance segmentation model for automated marine oil spill detection by Temitope Yekeen, S., Balogun, A.L., Wan Yusof, K.B.

“…The study concluded that the deep learning instance segmentation model performs better than conventional machine learning models and deep learning semantic segmentation models in detection and segmentation. …”
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Enhanced Reinforcement Learning Model for Extraction of Objects in Complex Imaging by Usmani, U.A., Roy, A., Watada, J., Jaafar, J., Aziz, I.A.

“…The visualization and classification of the area of interest in any picture is therefore an important function in order to segment the image. We examine a variety of image segmentation algorithms and give our reinforcement learning algorithm that uses Deep Convolutional Neural Networks for the detection of irregular objects, which has been tested on four datasets. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…This proposed algorithm achieved segmentation accuracy of 96.8% and 92.1% for ISIC and PH2 datasets respectively. …”
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