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

“…Second, the OpenVINO Inference Engine is utilized to optimize the trained models in order to facilitate real-time implementation. Third, the accurate tracking of each detected person is performed using the deep learning based tracking framework, known as DeepSORT. …”
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Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

“…At the same time, there has been growing interest from the research community in machine learning based detection of diseases using sequence based on gut microbiome data. …”
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Optimizing high-density aquaculture rotifer Detection using deep learning algorithm by Alixson Polumpung, Kit Guan Lim, Min Keng Tan, Sitti Raehanah Muhamad Shaleh, Renee Ka Yin Chin, Kenneth Teo Tze Kin

“…Second, is to develop the deep learning algorithm based on YOLOv3. Third step is to training and evaluate the model using loss function. …”
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Boundary extraction and corner point detection for map of kariah Kg. Bukit Kapar / 'Afina AmirHussin by AmirHussin, 'Afina

“…It is conclude that the FAST algorithm is better than Harris algorithm in terms of the amount of corner point detection and run time.…”
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A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network by Mustapha, Ibrahim

“…In this thesis, a Reinforcement Learning (RL) based clustering algorithm is proposed to address energy and Primary Users (PUs) detection challenges in CR-WSN. …”
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Review of Wheat Disease Classification and Severity Detection Models by Hongyan, Zang, Annie, Joseph, Shourong, Zhang, Rong, Liu, Wanzhen, Wang

“…This paper mainly aims to explain deep learning-based wheat diseases identification algorithm, and to discuss the benefits and drawbacks of present wheat disease detection approaches. …”
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Credit Card Fraud Detection Using New Preprocessing And Hybrid Machine Learning Techniques by Gasim, Esraa Faisal Malik

“…The second contribution to this research is to develop multiple hybrid machine learning models in order to enhance the detection of fraudulent activities in the credit card fraud detection domain.…”
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Indoor occupancy detection using machine learning and environmental sensors / Akindele Segun Afolabi ... [et al.] by Afolabi, Akindele Segun, Akinola, Olubunmi Adewale, Odetoye, Oyinlolu Ayomidotun, Adetiba, Emmanuel

“…As a result of these benefits, a plethora of machine learning-based solutions for occupancy detection has been developed in the literature. …”
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An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

“…The third proposed method is a new Evolutionary Neural Network (ENN) algorithm with a combination of Genetic Algorithm and Multiverse Optimizer (GAMVO) as a training part of ANN to create efficient anomaly-based detection with low false alarm rate. …”
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Multi-method diagnosis of CT images for rapid detection of intracranial hemorrhages based on deep and hybrid learning by Mohammed, Badiea Abdulkarem, Senan, Ebrahim Mohammed, Al-Mekhlafi, Zeyad Ghaleb, Rassem, Taha Hussein, Makbol, Nasrin M., Alanazi, Adwan Alownie, Almurayziq, Tariq S., Ghaleb, Fuad A., Sallam, Amer A.

“…The second proposed system using a hybrid technology consists of two parts: the first part is the GoogLeNet, ResNet-50 and AlexNet models for extracting feature maps, while the second part is the SVM algorithm for classifying feature maps. The third proposed system uses artificial neural networks (ANNs) based on the features of the GoogLeNet, ResNet-50 and AlexNet models, whose dimensions are reduced by a principal component analysis (PCA) algorithm, and then the low-dimensional features are combined with the features of the GLCM and LBP algorithms. …”
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Cloud-based lightweight detection of hardhat compliance based on YOLOv5 in power construction site by Wanbo, Luo

“…Therefore, it is necessary to provide real-time warnings when detecting workers without hardhats. Implementing deep learning-based object detection algorithms can facilitate the enforcement of hardhat-wearing compliance, thereby reducing work-related injuries and fatalities. …”
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Radiomics analysis and supervised machine learning model for classification of cervical cancer images using diffusion weighted imaging-MRI by Ramli, Zarina

“…Cervical cancer is the third most prevalent cause of mortality among women in Malaysia. …”
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Reactive approach for automating exploration and exploitation in ant colony optimization by Allwawi, Rafid Sagban Abbood

“…The third component is the ACO-based adaptive parameter selection algorithm to solve the parameterization problem which relies on quality, exploration and unified criteria in assigning rewards to promising parameters. …”
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Hybrid sampling and random forest machine learning approach for software detect prediction by Md. Anwar, Hossen, Md. Shariful, Islam, Nurhafizah, Abu Talip, Md. Sakib, Rahman, Fatema, Siddika, Mostafijur, Rahman, Sabira, Khatun, Mohamad Shaiful, Abdul Karim, S. M, Hasan Mahmud

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Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

“…In the third algorithm, a soft assignment technique using fuzzy encoding is used to transform low-level features into a higher-level feature representation. …”
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Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

“…However, analysis of mobile and wearable sensor data for human activity detection is still very challenging. This is further worsen by the use of single sensors modality and machine learning algorithms. …”
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Car dealership web application by Yap, Jheng Khin

“…The transfer learning algorithm pre-trained the River adaptive random forest regressor and classifier by transferring the tree structures and weights from the Scikit-learn fitted random forest regressor and classifier, respectively. …”
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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. …”

Artificial intelligence in diagnosing tuberculosis: a review by Meraj, Syeda Shaizadi, Yaakob, Razali, Azman, Azreen, Mohd Rum, Siti Nurulain, Ahmad Nazri, Azree Shahrel

“…In Artificial Intelligence (AI) various Machine Learning (ML) algorithms have furthered the interests in Computer-aided Detection (CADe) and Diagnosis (CADx) methods. …”
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A resource-aware content adaptation approach for e-learning environment / Mohd Faisal Ibrahim by Ibrahim, Mohd Faisal

“…The rapid growth of web and mobile technologies has allowed people to access E-Learning content from heterogeneous client devices. …”
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