Search Results - (( lesion classification based algorithm ) OR ( variable visualization based algorithm ))

Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC) by Ahmad, Faudziah, Ku-Mahamud, Ku Ruhana, Sainin, Mohd Shamrie, Airuddin, Ahmad

“…In this paper, an algorithm to classify leaf disease severity based on lesions is presented. …”
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Novel techniques for enhancement and segmentation of acne vulgaris lesions by Malik, A. S., Humayun, J., Kamel, N., Yap, F. B.-B.

“…The proposed algorithm is compared with two other methods. The proposed enhancement algorithm shows better result than both the other methods based on CIF and ICN. …”
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STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, SAMIR, EL-NAKLA, SADIQ A., ALHUWAIDI

“…Moreover, skin lesion images are clustered based on fused color, pattern and shape based features. …”
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Automated Segmentation And Classification Technique For Brain Stroke by Mohd Saad, Norhashimah, Abdullah, Abdul Rahim, Mohd Noor, Niza Suzaini, Mohd Ali, Nursabillilah

“…This study proposes a segmentation and classification technique to detect brain stroke lesions based on diffusion-weighted imaging (DWI). …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

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Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel by Mohammad Asaduzzaman , Rasel

“…This research is divided into two phases – 1) Feature Engineering phase explains skin conditions based on lesion segmentation and different dermoscopic feature extraction, while 2) Classification phase detects Melanoma. …”
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Enhanced Flipping Technique to Reduce Variability in Image Steganography by Kamil S., Abdullah S.N.H.S., Hasan M.K., Bohani F.A.

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

“…A hybrid segmentation technique, fuzzy c-means with active contour (FCMAC), is proposed to enhance lesion localization accuracy. 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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ENGINEERING DESIGN WITH PSO ALGORITHM by MHD BASIR, SITI NUR HAJAR

“…It assists design engineers as it gives a clearer visualization to predict which value of the variables gives a best produced result. …”
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Damage visualization based on frequency shift of single-mode ultrasound-guided wavefield by Shahrim, Muhamad Azim, Harmin, Mohammad Yazdi, Romli, Fairuz Izzuddin, Chia, Chen Ciang, Jung-Ryul, Lee

“…However, the challenge lies in the complexity of the algorithm for mode isolation. For this study, the damage visualization is performed based on frequency shift of single-mode ultrasound-guided wavefield. …”
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Automatic control of flotation process using computer vision by Saravani, Ali Jahed

“…A froth model correlating the image variables to process variables and a prediction system estimating the metallurgical parameters based on image variables were then developed by using a neural network structure. …”
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer by Tehseen Mazhar, Inayatul Haq, Allah Ditta, Syed Agha Hassnain Mohsan, Faisal Rehman, Imran Zafar, Jualang Azlan Gansau, Lucky Poh Wah Goh

“…This article describes the fundamentals of ML-based implementations, as well as future limits and concerns for the production of skin cancer detection and classification systems. …”
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Computer-assisted pterygium screening system: a review by Abdani, Siti Raihanah, Zulkifley, Mohd Asyraf, Shahrimin, Mohamad Ibrani, Zulkifley, Nuraisyah Hani

“…The deep learning networks have been successfully implemented for three major purposes, which are to classify an image regarding whether there is the presence of pterygium tissues or not, to localize the lesion tissues through object detection methodology, and to semantically segment the lesion tissues at the pixel level. …”
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Mathematical snalysis of blood vessels segmentation based on three retinal images datasets by Bilal, Sara Mohammed Osman Saleh, Munir, Fatin, Khalifa, Othman Omran

“…The results show that measuring the automatic segmentation algorithm performance is based mainly on how the retinal images are acquired as well as the image processing technique used for segmentation. …”
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TB-FusionNet: a multi-scale feature fusion algorithm with spatial and channel cross-attention for tuberculosis detection by Ding, Zeyu, Yaakob, Razali, Tieng Wei, Koh, Azman, Azreen, Mohd Rum, Siti Nurulain, Zakaria, Nor Fadhlina, Ahmad Nazri, Azree Shahril

“…To address the aforementioned issues, this study proposes TB-FusionNet, a multi-scale feature fusion algorithm based on channel and spatial cross-attention mechanisms, for tuberculosis classification. …”
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Development of a Prediction Algorithm using Boosted Decision Trees for Earlier Diagnoses on Obstructive Sleep Apnea by Sim, Doreen Ying Ying

“…The parameters involved in the prediction algorithms developed are based on common OSA risk factors and visual-inspected variables found in the patients’ records in the OSA datasets collected. …”
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Healthcare professional in the loop (HPIL): Classification of standard and oral cancer-causing anomalous regions of oral cavity using textural analysis technique in autofluorescenc... by Awais, M., Ghayvat, H., Krishnan Pandarathodiyil, A., Nabillah Ghani, W.M., Ramanathan, A., Pandya, S., Walter, N., Naufal Saad, M., Zain, R.B., Faye, I.

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Healthcare professional in the loop (HPIL): Classification of standard and oral cancer-causing anomalous regions of oral cavity using textural analysis technique in autofluorescenc... by Awais, M., Ghayvat, H., Krishnan Pandarathodiyil, A., Nabillah Ghani, W.M., Ramanathan, A., Pandya, S., Walter, N., Naufal Saad, M., Zain, R.B., Faye, I.

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Physically-Based Animation in Performing Accuracy Bouncing Simulation by Loh, Ngiik Hoon

“…Animation based physics algorithm provided the animator the ability to control the realism of animation without setting the key frame manually, to provide an extra layer of visually convincing simulation.…”
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Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

“…The performance of algorithms was measured based on classification accuracy, error rate, and precision and recall. …”
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