Search Results - (( based segmentation using algorithm ) OR ( data classification problems algorithm ))

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

“…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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Quranic diacritic and character segmentation and recognition using flood fill and k-nearest neighbors algorithm by Alotaibi, Faiz E A L

“…The diacritic detections are performed using a region-based algorithm with 89% accuracy and 95% improved by using flood fill segmentations method. 2DMED feature extraction accuracy was 90% for diacritics and 96% improved by applied CNN. …”
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Applying SAX-based time series analysis to classify EEG signal using a COTS EEG device by Shanmuga, Pillai A/L Murutha Muthu

“…SAX algorithm changes the original time series data into a symbolic string and perform the discretization by dividing a time series into equal-sized segments. …”
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Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification by Al-Sharhan, Salah, Bimba, Andrew

“…The proposed approach in this work tends to tackle the multiple EEG channels problem by segmenting the EEG signals in the frequency domain based on changing spikes rather than the traditional time based windowing approach. …”
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Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification by Ahmad, Fadzil

“…Based on the occurrences of the best result obtained by an algorithm across different test functions; it is proven that the proposed method outperforms standard GA. …”
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New Algorithm of Location Model based on Robust Estimators and Smoothing Approach by Hamid, Hashibah

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An automated high-accuracy detection scheme for myocardial ischemia based on multi-lead long-interval ECG and Choi-Williams time-frequency analysis incorporating a multi-class SVM... by Hussein, Ahmed Faeq, Hashim, Shaiful Jahari, Rokhani, Fakhrul Zaman, Wan Adnan, Wan Azizun

“…The classification process uses the data of 92 normal and 266 patients from four different databases. …”
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Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Audrey Huong, Kim Gaik Tay, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

“…This work compared manual segmentation with our proposed hybrid automatic segmentation method (HHM) for this classification problem. …”
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Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Audrey Huong, Kim Gaik Tay, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

“…This work compared manual segmentation with our proposed hybrid automatic segmentation method (HHM) for this classification problem. …”
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Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Kim Gaik Tay, Audrey Huong, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

“…This work compared manual segmentation with our proposed hybrid automatic segmentation method (HHM) for this classification problem. …”
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Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Audrey Huong, Kim Gaik Tay, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

“…This work compared manual segmentation with our proposed hybrid automatic segmentation method (HHM) for this classification problem. …”
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Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Kim Gaik Tay, Audrey Huong, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

“…This work compared manual segmentation with our proposed hybrid automatic segmentation method (HHM) for this classification problem. …”
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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

“…The development of ML algorithms in dermatology has been supported lately regarding links to digital data processing (e.g., electronic medical records, Image Archives, omics), quicker computing and cheaper data storage. …”
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Computer aided diagnoses for detecting the severity of Keratoconus by Abdullah, Osamah Qays, Boughariou, Aicha, Al-Azawi, Fadia W., Al-Araji, Ahmed Mohammed Khadum Abdulamer, Mehdy, Mehdy Mwaffeq

“…A P-value of <0.001 indicated significant and clear link between KC stages and pathologic ratio. Conclusion: The algorithm used for extracting the cone base area of the keratoconic cornea at different stages was validated by an ophthalmic specialist to ensure that the cone base area was appropriately extracted. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

“…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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A derivative-free optimization method for solving classification problem by Shabanzadeh, Parvaneh, Abu Hassan, Malik, Leong, Wah June

“…Problem statement: The aim of data classification is to establish rules for the classification of some observations assuming that we have a database, which includes of at least two classes. …”
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