Search Results - (( intelligence based cdss algorithm ) OR ( intelligence valid mapping algorithm ))

Leveraging CQT-VMD and pre-trained AlexNet architecture for accurate pulmonary disease classification from lung sound signals by Neili, Zakaria, Sundaraj, Kenneth

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Tacit knowledge for business intelligence framework using cognitive-based approach by Surbakti, Herison

“…The framework is validated through Power BI and reviewed by seven experts. …”
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An application of image processing for automated mixed household waste sorting system by Zol Bahri, Razali, Madasamy, Gunasegaran

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Hybrid Spatial-Artificial Intelligence Approach for Renewable Energy Sources Sites Identification and Integration in Sarawak State by Far Chen, Jong

“…The minimum total distances in all four cases are acquired and validated as both the TSP-GA algorithm and the Traveling Salesman Problem-Mixed Integer Linear Programming (TSP-MILP) algorithm produced the same routing pattern. …”
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Artificial intelligent power prediction for efficient resource management of WCDMA mobile network by Tee Y.K., Tinng S.K., Koh J., David Y.

“…This artificial intelligent call admission control (CAC) was validated using a dynamic WCDMA mobile network simulator. …”

Flood mapping based on novel ensemble modeling involving the deep learning, Harris Hawk optimization algorithm and stacking based machine learning by Costache R., Pal S.C., Pande C.B., Islam A.R.M.T., Alshehri F., Abdo H.G.

Genetic neuro controller based direct torque control for switched reluctance motor drive by Veena, P, Jeyabharath, R, Rajaram, M, Sivanandam, S.N.

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LSR-YOLO: a lightweight and fast model for retail products detection by Zhao, Yawen, Solihin, Mahmud Iwan, Yang, Defu, Cai, Bingyu, Chow, Li Sze, Handayani, Dini Oktarina Dwi, Prabuwono, Anton Satria

“…Experiments on the Locount dataset demonstrate that LSR-YOLO achieves an inference speed of 357.1 FPS with mAP50 of 72.2% and mAP50-95 of 47.8%. Compared with the baseline YOLOv8n, LSR-YOLO increases inference speed by 246.7 FPS, making it substantially faster and more suitable for real-time retail applications. …”
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Design and development of latex mark visual detection system by Chong, Kai Zhe, Zakaria, Azrul Abidin, Mohamed, Hassan, Baharuddin, Mohd Zafri

“…With the 14 stages of algorithm development, including tagging and training, the YOLO v5 model achieved an average loss of 5.2% and mAP performance of 99.3% accuracy, achieving the AQL 2.5 standard with less than 15 pieces of false detection.…”
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Development of an accurate AI-based dermatology assistant for skin disease recognition using YOLOv8 models by Huzaini, Muhammad Irfan Darwish, Mansor, Hasmah, Gunawan, Teddy Surya, Ahmad, Izanoordina

“…After 500 training epochs, the YOLOv8 Small Model was the most accurate, achieving a precision of 84%, a recall of 77.1%, and a mean average precision (mAP) of 84%. The potential of the proposed AI-based assistant to significantly improve healthcare accessibility and diagnostic accuracy in underserved areas is demonstrated through rigorous testing, which validates its effectiveness. …”
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Enhancing Driving Assistance System with YOLO V8-Based Normal Visual Camera Sensor by Beg, Mohammad Sojon, Muhammad Yusri, Ismail, Miah, Md Saef Ullah, Mohamad Heerwan, Peeie

“…After conducting a performance validation, the system achieved a mean average precision (mAP) of 88.2% on train dataset and was able to detect different types of vehicles such as cars, motorcycles, and traffic lights. …”
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Disease detection of solanaceous crops using deep learning for robot vision by Ahmad Radzi, Syafeeza, A.Halim, Nurul Hidayah, Abd Razak, Norazlina, Mohd Saad, Wira Hidayat, Wong, Yan Chiew, Amsan, Azureen Naja

“…The performances of YOLOv5 were more robust in terms of 94.2% mAP, and the speed was slightly faster than Scaled-YOLOv4. …”
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Dental Age Estimation Using a Convolutional Neural Network Algorithm on Panoramic Radiographs: A Pilot Study in Indonesia by Arofi Kurniawan, Michael Saelung, Beta Novia Rizky, An’nisaa Chusida, Beshlina Fitri Widayanti Roosyanto Prakoeswa, Giselle Nefertari, Ariana Fragmin Pradue, Mieke Sylvia Margaretha, Aspalilah Alias, Anand Marya

Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

“…This research also proposed an intelligent and robust classification technique to classify the MRI scans as normal or abnormal and also for validation purpose. …”
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Stereo Camera-Based Aerial Target Geolocation in a Ground-Based Platform Environment by Amir Hilmi Bin Ahmad Azizi

Implementation of YOLOv8-seg on store products to speed up the scanning process at point of sales by Hanna Arini, Parhusip, Suryasatriya, Trihandaru, Denny, Indrajaya, Jane, Labadin

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Retinal Microvascular Feature Extraction Using Faster Region-based Convolutional Neural Network by Mohammed Enamul, Hoque

“…The retinal images were taken from the different public databases to train, test, and validate the performance of this proposed method. This proposed method obtained 91.82% Mean Average Precision (mAP), 92.81% sensitivity, and 63.34% Positive Predictive Value (PPV). …”
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Glove defect detection via YOLO V5 by Yong, Chen How, Ahmad Fakhri, Ab. Nasir, Khairul Fikri, Muhammad, Anwar P. P., Abdul Majeed, Mohd Azraai, Mohd Razman, Muhammad Aizzat, Zakaria

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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

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Ant-based vehicle congestion avoidance framework using vehicular networks / Mohammad Reza Jabbarpour Sattari by Sattari, Mohammad Reza Jabbarpour

“…AVCAF collects real-time traffic data through vehicular networks to consider non-recurring congestion conditions in its routing mechanism via ant-based algorithm. The proposed framework is evaluated and validated through simulation environment. …”
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