Search Results - (( evolution optimisation based algorithm ) OR ( frames detection learning algorithm ))

Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…Also, the current motion target detection algorithms extract features from the relevant object only if the moving object has complex texture features. …”
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Social Distancing Detection with Deep Learning Model by Hou Y.C., Baharuddin M.Z., Yussof S., Dzulkifly S.

Overhead view based person counting using deep learning by Kaw, Chee Zhao

“…Third, the accurate tracking of each detected person is performed using the deep learning based tracking framework, known as DeepSORT. …”
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An integrated deep learning deepfakes detection method (IDL-DDM) by Yassin, Warusia, Johan, Azwan, Abas, Zuraida Abal, Baharon, Mohd Rizuan, Bejuri, Wan, Ismail, Anuar

“…The proposed IDL-DDM comprises side-by-side deep learning algorithms such as Multilayer Perceptron and Convolutional Neural Network (CNN). …”
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Fast shot boundary detection based on separable moments and support vector machine by Idan, Zinah N., Abdulhussain, Sadiq H., Mahmmod, Basheera M., Al-Utaibi, Khaled A., Syed Abdul Rahman Al-, Syed Abdul Rahman Al-Hadad, Sait, Sadiq M.

“…As a result, the computational cost is reduced in the subsequent stages. Finally, machine learning statistics based on the support vector machine is implemented to detect the cut transitions. …”
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Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm by Ismail, Asmida, Ahmad, Siti Anom, Che Soh, Azura, Hassan, Mohd Khair, Harith, Hazreen Haizi

“…This paper presented an analysis performance of deep learning object detector by combining a deep learning Convolutional Neural Network (CNN) for object classification and applies classic object detection algorithms to devise our own deep learning object detector. …”
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Vibration Signal for Bearing Fault Detection using Random Forest by Abedin T., Koh S.P., Yaw C.T., Phing C.C., Tiong S.K., Tan J.D., Ali K., Kadirgama K., Benedict F.

“…Based on the chosen properties of an induction motor, a random forest (RF) classifier, a machine learning technique, is examined in this study for bearing failure detection. …”

A competitive co-evolutionary approach for the nurse scheduling problem by Mohamad Nazri, Maizatul Farhana, Mohd Yusoh, Zeratul Izzah, Basiron, Halizah, Daud, Azlina

“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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Development of automatic obscene images filtering using deep learning by Awad, Abdelrahman Mohamed, Gunawan, Teddy Surya, Habaebi, Mohamed Hadi, Ismail, Nanang

“…This paper proposes a fully automated method to filter any storage device from obscene vid-eos and images using deep learning algorithms. The whole recognition process can be divided into two stages, including fine detection and focus detection. …”
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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

“…Classical computer vision algorithms for detection holds limitation in robustness and scalability. …”
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Image processing based vehicle detection and tracking method by Bhaskar, P.K., Yong, S.-P.

“…First, we differentiate the foreground from background in frames by learning the background. Here, foreground detector detects the object and a binary computation is done to define rectangular regions around every detected object. …”
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Computer vision that can ‘see’ in the dark by Wong, Yan Chiew, Ahmad Radzi, Syafeeza, Goh, Shi Yong, Sarban Singh, Ranjit Singh

“…A hybrid model of integrating convolutional neural network (CNN) into YOLOv7 has been proposed. YOLOv7 is an algorithm designed for real-time object detection in image or video, for fast and accurate detection in applications such as autonomous vehicles and surveillance systems. …”
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Home intruder detection system using machine learning and IoT by Sahlan, Fadhluddin, Feizal, Faeez Zimam, Mansor, Hafizah

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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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A real-time mobile notification system for inventory stock out detection using SIFT and RANSAC by Merrad, Yacine, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Gunawan, Teddy Surya

“…It may mean the detection of an object within a frame and classify it (human, animal, vehicle, building, etc) by the use of some algorithms. …”
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Passenger Counting With Face Detection by Teoh, Han Wei

“…MobileNet-single shot detector (SSD) is chosen as the object detector model since it belongs to a class of efficient models that can execute on mobile and embedded systems. While running detections across every video frames, centroid tracking algorithm tracks every unique person in video streams, where Kalman filter is further applied to reduce the noise. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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