Search Results - (( between ((learning algorithm) OR (learning algorithms)) ) OR ( between matching algorithm ))

Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

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A new text-based w-distance metric to find the perfect match between words by Ali, M., Jung, L.T., Hosam, O., Wagan, A.A., Shah, R.A., Khayyat, M.

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A new function of stereo matching algorithm based on hybrid convolutional neural network by Hamid, Mohd Saad, Kadmin, Ahmad Fauzan, Abd Manap, Nurulfajar, Hamzah, Rostam Affendi, Abd Gani, Shamsul Fakhar, Herman, Adi Irwan

“…This paper proposes a new hybrid method between the learning-based and handcrafted methods for a stereo matching algorithm. …”
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AR oriented pose matching mechanism from motion capture data by Iqbal J., Sidhu M.S., Ariff M.B.M.

“…The experimental results show that the proposed algorithm outperforms the state of art techniques for successful identification and recognition of matched pose between the dance trainer and the expert of the pre-recorded video through the Kinect sensor. � 2018 Authors.…”

Stereo matching algorithm using deep learning and edge-preserving filter for machine vision by Abd Gani, Shamsul Fakhar, Miskon, Muhammad Fahmi, Hamzah, Rostam Affendi, Hamid, Mohd Saad, Kadmin, Ahmad Fauzan, Herman, Adi Irwan

“…This paper proposes a hybrid method of a stereo matching algorithm with the goal of generating an accurate disparity map critical for applications such as 3D surface reconstruction and robot navigation to name a few. …”
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Music Recommender System Using Machine Learning Content-Based Filtering Technique by Foong, Kin Hong

“…These are the popular algorithm for unsupervised learning, a machine learning method to analyse and cluster datasets. …”
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A Comparative of Two-Dimensional Statistical Moment Invariants Features in Formulating an Automated Probabilistic Machine Learning Identification Algorithm for Forensic Application by Zun Liang, Chuan, David, Chong Teak Wei, Connie, Lee Wai Yan, Muhammad Fuad Ahmad, Nasser, Nor Azura Md, Ghani, Abdul Aziz, Jemain, Choong-Yeun, Liong

“…Moreover, the proposed identification algorithm is also tested in different scenarios, including based on the classification of strength association measurements between the extracted feature sets. …”
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Recognition of human motion from qualitative normalised templates by Chan, C.S., Liu, H., Brown, D.J.

“…In contrast to other human motion classification methods which usually include a human model, prior knowledge on human motion and a matching algorithm, we replace the matching algorithm (e.g. template matching) with the proposed QNTs. …”
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Refining disparity maps using deep learning and edge-aware smoothing filter by Abd Gani, Shamsul Fakhar, Miskon, Muhammad Fahmi, Hamzah, Rostam Affendi, Hamid, Mohd Saad, Kadmin, Ahmad Fauzan, Herman, Adi Irwan

“…Stereo matching algorithm is crucial for applications that rely on three-dimensional (3D) surface reconstruction, producing a disparity map that contains depth information by computing the disparity values between corresponding points from a stereo image pair. …”
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Predicting Cheaters in PlayerUnknown’s Battlegrounds (PUBG) using Random Forest Algorithm by Nurin Alya, Haris

“…The primary goal is to use the Random Forest algorithm, an effective machine learning technique, to predict instances of cheating based on the behavioural patterns of participants. …”
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Characterization of oil palm fruitlets using artificial neural network by Olukayode, Ojo Adedayo

“…The results also showed that contrary to the widely reported gap between the accuracy of the LM algorithm and other feed forward neural network training algorithms, the RP trained network performed as good as that of the LM algorithm for the range of data considered. …”
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Stereo matching algorithm based on deep learning: a survey by Hamzah, Rostam Affendi, Hamid, Mohd Saad, Kadmin, Ahmad Fauzan, Abd Manap, Nurulfajar

“…Hence, this article presents a survey on the algorithm frameworks related to the stereo matching algorithm. …”
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Improving the diagnostic accuracy for major depressive disorder using machine learning algorithms integrating clinical and near-infrared spectroscopy data by Ho, C.S., Chan, Y.L., Tan, T.W., Tay, G.W., Tang, T.B.

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Real Time Tracking and Face Recognition Using Web Camera by Thirunavakkarasu, Punithavathi

“…Eigenface method combined with neural networks displays good performance in terms of accuracy and the ability for learning and generalization. The tracking system works well for objects traveling speeds below 5mIs and at distances from between 0.5m to 2m from the camera. …”
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Joint optimization of resources allocation for quality of service aware next-generation heterogeneous cellular networks / Hayder Faeq Rasool Alhashimi by Hayder Faeq Rasool , Alhashimi

“…Finally, a State-Action-Reward-State-Action (SARSA) algorithm, which is a reinforcement learning approach, is proposed to solve the power allocation optimization problem. …”
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Novel reservoir system simulation procedure for gap minimization between water supply and demand by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, El-Shafie, Ahmed

“…In this research, an optimization algorithm, namely, the shark machine learning algorithm (SMLA) that has high inertia for obtaining its targets, is proposed that mimics the natural shark process. …”
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Android Mobile Malware Classification Based on System Call and Permission Using Tokenization by Intan Nurfarahin Binti Ahmad

A comparative sales forecast study between supervised and unsupervised learning algorithm on restaurant / Azhar Tamby by Tamby, Azhar

“…In this research, there are two algorithm of neural network will be used. It is coming from supervised and unsupervised learning algorithm. …”
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Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: a cross-sectional SHAP-based analysis of NHANES 2009-2023 by Tang, Yan, Jia, Lei, Zhou, Junjun, Dou, Jin, Qian, Jingjuan, Yi, Xin, Soh, Kim Lam

“…Variable selection was performed using least absolute shrinkage and selection operator regression. Five machine learning algorithms - random forest, extreme gradient boosting (XGBoost), multilayer perceptron, logistic regression, and support vector machine - were trained and evaluated using 5-fold cross-validation. …”
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Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective by Abubakar, Adamu, Ya’u Gital, Abdulsalam, Chiroma, Haruna, Rana, Nadim, Abdulhamid, Shafi’i, Muhammad, Amina Nuhu, Umar, Aishatu Yahaya

“…We believed that the survey can facilitate synergy between the nature inspired algorithms and deep learning research communities. …”
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