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

“…Image segmentation is the process of segmenting an image into the region of interest. …”
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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.

“…The review coverage includes the initial screening and imaging techniques, image pre-processing, segmentation techniques based on machine learning and deep learning techniques. …”
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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.

“…The review coverage includes the initial screening and imaging techniques, image pre-processing, segmentation techniques based on machine learning and deep learning techniques. …”
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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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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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A Reinforcement Learning Algorithm for object segmentation in complex images by Usmani, Usman Ahmad

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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…Therefore, this research has developed an improved edge detection and contour segmentation algorithm that is able to correctly segment various objects from both indoor and outdoor images. …”
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Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation by Alia, Osama Moh’d Radi

“…Fuzzy clustering algorithms, which fall under unsupervised machine learning, are among the most successful methods for image segmentation. …”
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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 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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How Does Image Complexity Affect the Accuracy of an Interactive Image Segmentation Algorithm? by Kok Luong, Goh, Soo See, Chai, Muzaffar, Hamzah, Emily Sing, Kiang Siew

“…This study investigates the impact of image complexity on the accuracy of interactive image segmentation algorithms. …”
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Deep Learning Based image segmentation for expensive soil desiccation crack recognition and qualification by Ling, Hui Yean

“…The objectives of the study included designing soil desiccation experiment setup for desiccation crack image acquisition, evaluating crack imaging analysis based on deep learning algorithms, and quantifying desiccation cracks through image processing techniques. …”
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Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images by Jabar F.H.A., Ismail W., Salam R.A., Hassan R.

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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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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…Multi-layer perceptron (MLP) neural network trained using backpropagation algorithm is used to segment the color image. The results of color segmentation show that the algorithm is able to segment the images reliably with less appearance of small blobs. …”
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A study of left ventricular (LV) segmentation on cardiac cine-MR images by Ahad, Md Atiqur Rahman, Jahan, Israt

“…In this paper, we explore several state-of-the-art segmentation algorithms applied on left ventricular (LV) segmentation on cardiac cine-MR images. …”
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A comparative study of interactive segmentation with different number of strokes on complex images by Kok, Luong Goh, Giap, Weng Ng, Muzaffar Hamzah, Soo, See Chai

“…The use of the same number of strokes on the object of interest and background on three interactive segmentation algorithms: i) Nonparametric Higher-order Learning (NHL), ii) Maximal Similarity-based Region Merging (MSRM) and iii) Graph-Based Manifold Ranking (GBMR) are evaluated, focusing on the complex images from Berkeley image dataset. …”
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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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A Comparative Study of Interactive Segmentation with Different Number of Strokes on Complex Images by Goh, Kok Luong, Ng, Giap Weng, Muzaffar, Hamzah, Chai, Soo See

“…The use of the same number of strokes on the object of interest and background on three interactive segmentation algorithms: i) Nonparametric Higher-order Learning (NHL), ii) Maximal Similarity-based Region Merging (MSRM) and iii) GraphBased Manifold Ranking (GBMR) are evaluated, focusing on the complex images from Berkeley image dataset. …”
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