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Ensemble learning of deep learning and traditional machine learning approaches for skin lesion segmentation and classification by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, Hiren, Mewada, Muhammad Abid, Sherazi

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Segmentation Word to Improve Performance Sentiment Analysis for Indonesian Language by Siti Mujilahwati, Siti Mujilahwati, M. Safar, Noor Zuraidin, Supriyanto, Catur

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River segmentation with Atrous Convolution via DeepLabv3 / Nur Adilah Hamid by Hamid, Nur Adilah

“…The Deep Learning segmentation algorithm DeepLabv3 and DeepLabv3+ are trained and tested for the task of water segmentation and the performances are compared with previous works. …”
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Deep learning-based item classification for retail automation by Ling, Ji Xiang

“…Real-time processing was achieved through the integration of object detection algorithms like YOLO and image segmentation techniques. …”
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Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks by Ayomide, Kabirat Sulaiman, Mohd Aris, Teh Noranis, Zolkepli, Maslina

“…Finally, a hybrid approach of GoogLeNet deep learning algorithm and Convolution Neural Network- Support Vector Machines (CNN-SVM) deep learning is performed to increase the accuracy of tumor classification. …”
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Hybridization of SLIC and extra tree for object based image analysis in extracting shoreline from medium resolution satellite images by Abd Manaf, Syaifulnizam, Mustapha, Norwati, Sulaiman, Md. Nasir, Husin, Nor Azura, Mohd Shafri, Helmi Zulhaidi, Razali, Mohd Norhisham

“…The performance of the segmentation algorithms and machine learning classifiers were assessed in terms of segmentation time and overall accuracy in four experimental settings comprising of three different parameters. …”
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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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EMG Signals Classification on Human Activity Recognition using Machine Learning Algorithm by Nurhanim, K., Elamvazuthi, I., Izhar, L.I., Capi, G., Su, S.

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Development of river water level estimation from surveillance cameras for flood monitoring system using deep learning techniques by Muhadi, Nur 'Atirah

“…Hence, deep learning technique was chosen for water segmentation procedure in this work. …”
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DeepPulmoTB: a benchmark dataset for multi-task learning of tuberculosis lesions in lung computerized tomography (CT) by Tan, Zhuoyi, Madzin, Hizmawati, Norafida, Bahari, ChongShuang, Yang, Sun, Wei, Nie, Tianyu, Cai, Fengzhou

“…To demonstrate the advantages of DeepPulmoTB, we propose a novel multi-task learning model, DeepPulmoTBNet (DPTBNet), for the joint segmentation and classification of lesion tissues in CT images. …”
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Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images by Mohd Saad, Norhashimah, Azman, Izzatul Husna, Abdullah, Abdul Rahim, Hamzah, Rostam Affendi, Muda, Ahmad Sobri, Yamba, Farzanah Atikah

“…For classification, the system evaluates traditional machine learning algorithms like support vector machine (SVM) and k-nearest neighbor (KNN), alongside deep learning models such as convolutional neural network (CNN) and bilayered neural network (BNN). …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Development of gender and race recognition system using speech and recognition by using frequency spectrum by Ng Siew Fong

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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower by Gatea, Sarah Jabbar

“…Damaging the full-scale tower is not practical; thus, two different parts of the tower segments and their connections (1-2 and 2-3) are considered and tested experimentally with and without damage to validate the capability of the developed hybrid algorithm to detect damage. …”
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A review of Convolutional Neural Networks in Remote Sensing Image by Liu, Xinni, Han, Fengrong, Kamarul Hawari, Ghazali, Izzeldin, I. Mohd, Zhao, Yue

“…Recently, convolutional neural network based deep learning algorithm has achieved a series of breakthrough research results in the fields of objective detection, image semantic segmentation and image classification, etc. …”
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Heart murmur detection using supervised machine learning by Moulana, Saad Hafez, Luqman, Ahmad, Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Wani, Sharyar, Ibrahim, Adamu Abubakar

“…When trained and validated, the algorithm showed results of that train score 70.0%, test score 68.0% and validation 70.0%.…”
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Using Machine Learning to Optimize Green Influencer Marketing Strategies: A Study of Consumer Behavior Trends by Neetu, Sharma

“…Most respondents expressed willingness to purchase green products when the messaging was authentic and well-targeted. Moreover, ML algorithms were instrumental in identifying top-performing influencers, segmenting audiences by green preferences, and personalizing recommendations, which enhanced engagement and conversion rates. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Prediction of ADHD from a small dataset using an adaptive EEG theta/beta ratio and PCA feature extraction by Sase, Takumi, Othman, Marini

“…Due to the heterogeneity of ADHD symptoms, several studies have applied machine learning algorithms for enhancing the recognition of ADHD. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…Validation included both machine learning evaluation and expert feedback. Machine learning results showed strong performance, with Random Tree and PART delivering the most reliable predictions. …”
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