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Segmentation of pulmonary cavity in lung CT scan for tuberculosis disease by Tan, Zhuoyi, Madzin, Hizmawati, Khalid, Fatimah, Beng, Ng Seng

“…Then, based on this threshold, the lesion tissue within the bounding box is extracted and forms a mask that can be used for semantic segmentation tasks. Finally, we use the generated TB semantic segmentation mask to train Unet and Vnet models to verify the effectiveness of the algorithm. …”
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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.

“…Second, the datasets taken for the semantic segmentation task are not balanced since certain classes are present more than the others. …”
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Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach by Vadiveloo, Mogana

“…Region merging approach is used to reduce over segmented regions produced by region-based image segmentation algorithms. …”
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2TSS: Two-tier semantic segmentation framework with enhancement for hotspot detection of solar photovoltaic thermal images by Nurul Huda, Ishak, Iza Sazanita, Isa, Muhammad Khusairi, Osman, Mohd Shawal, Jadin, Kamarulazhar, Daud, Mohd Zulhamdy, Ab Hamid

“…However, the semantic segmentation approach has limitations in terms of accuracy, particularly for hotspot thermal images. …”
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An Optimized Semantic Segmentation Framework for Human Skin Detection by Huong, Audrey, Ngu, Xavier

“…The study incorporating optimization strategy in semantic segmentation is underexplored in dermatology. …”
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Malaria parasites segmentation in red blood cells images using mean-shift and median-cut by Tn. Muda, Tn. Zalizam, A Salam, Rosalina

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Modelling semantic context for novelty detection in wildlife scenes by Yong, SP, Deng, JD, Purvis, MP

“…Working with wildlife image data, the framework starts with image segmentation, followed by feature extraction and classification of the image blocks extracted from image segments. …”
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Determination of the onset of ventricular tachycardia by Mohd Afzan, Othman, Norlaili, Mat Safri, Sinan S., Mohammed Sheet

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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.

“…So far, detection and discrimination of oil spill and look-alike are still limited to the use of traditional machine learning algorithms and semantic segmentation deep learning models with limited accuracy. …”
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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.

“…So far, detection and discrimination of oil spill and look-alike are still limited to the use of traditional machine learning algorithms and semantic segmentation deep learning models with limited accuracy. …”
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Effective query structuring with ranking using named entity categories for XML retrieval by Roko, Abubakar

“…The method employs Semantic Tags Extraction (STSE) algorithm to extract semantic tags of an element and Element Enrichment (EERM) algorithm to enrich the elements. …”
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Enhanced Deep Learning Framework for Fine-Grained Segmentation of Fashion and Apparel by Usmani, U.A., Happonen, A., Watada, J.

“…The low-level feature data are extracted by the feature extraction module using Mask Region Convolutional Neural Network (RCNN) segmentation branches and Inception V3 used to extract the high-level semantic data. …”
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Deep learning semantic segmentation for water level estimation using surveillance camera by Muhadi, Nur 'Atirah, Abdullah, Ahmad Fikri, Bejo, Siti Khairunniza, Mahadi @ Othman, Muhammad Razif, Mijic, Ana

“…This work presented two well-established deep learning algorithms, DeepLabv3+ and SegNet networks, and evaluated their performances using several evaluation metrics. …”
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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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Word segmentation of output response for sign language devices by Za'bah, Nor Farahidah, Muhammad Nazmi, Ahmad Amierul Asyraf, Azman, Amelia Wong

“…The proposed text segmentation method in this work is by using the dynamic programming and back-off algorithm, together with the probability score using word matching with an English language text corpus. …”
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Automated visual defect detection using deep learning by Loh, Xiao

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Deep learning segmentation of brain ischemic lesion from magnetic resonance images for three-dimensional modelling by Muhammad Ismaill, Mat Lizah, Nasrul Hadi, Johari, Mohd Jamil, Mohamed Mokhtarudin

“…The existing segmentation algorithm is limited due to its computationally expensiveness in achieving a small accuracy. …”
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The automatic focus segmentation of multi-focus image fusion by Kamarul Hawari, Ghazali, Ismail, .

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Deep learning-based water segmentation for autonomous surface vessel by Mohd Adam, Muhammad Ammar, Ibrahim, Ahmad Imran, Zainal Abidin, Zulkifli, Mohd Zaki, Hasan Firdaus

“…In this work, the deep learning models based on Convolutional Neural Network (CNN) to implement binary semantic segmentation is studied. This architecture identifies each pixel to water and non-water classes. …”
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Development of brain tumor segmentation of magnetic resonance imaging (MRI) using u-net deep learning by Jwaid W.M., Al-Hussein Z.S.M., Sabry A.H.

“…The developed U-Net architecture has been applied on the MRI scan brain tumor segmentation dataset in MICCAI BraTS 2017. The results using Matlab-based toolbox indicate that the proposed architecture has been successfully evaluated and experienced for MRI datasets of brain tumor segmentation including 336 images as training data and 125 images for validation. …”