Search Results - (( using convolutional methods algorithm ) OR ( based optimization method algorithm ))

Stereo matching algorithm based on hybrid convolutional neural network and directional intensity difference by Hamid, Mohd Saad, Abd Manap, Nurulfajar, Hamzah, Rostam Affendi, Kadmin, Ahmad Fauzan

“…The proposed algorithm contains a deep learning-based method and a handcrafted method. …”
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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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Vehicle detection for vision-based intelligent transportation systems using convolutional neural network algorithm by Khalifa, Othman Omran, Wajdi, Muhammad H., Saeed, Rashid A., Hassan Abdalla Hashim, Aisha, Ahmed, Muhammed Z., Ali, Elmustafa Sayed

“…Software based solutions using traditional algorithms such as Histogram of Gradients (HOG) and Gaussian Mixed Model (GMM) are computationally slow and not suitable for real-time traffic detection. )erefore, the paper will review and evaluate different vehicle detection methods. …”
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Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm by Jaber M.M., Yussof S., Elameer A.S., Weng L.Y., Abd S.K., Nayyar A.

A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…In addition, the confidence level was built using the percentile-t-method (or bootstrap-t-method). …”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq by Uzair , Ishtiaq

“…Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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Analysis of online CSR message authenticity on consumer purchase intention in social media on Internet platform via PSO-1DCNN algorithm by Li, Man, Liu, Fang, Abdullah, Zulhamri

“…This work proposes an algorithm based on PSO-1DCNN joint optimization to analyze the impact of online CSR information authenticity on consumers’ purchase intention in social media on the Internet platform. …”
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Integrated deep learning for cardiovascular risk assessment and diagnosis: An evolutionary mating algorithm-enhanced CNN-LSTM by Ahmed Alsarori, Ahmed Mohammed, Mohd Herwan, Sulaiman

“…This study proposes a dual-output deep learning model based on a hybrid Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model, optimized using the Evolutionary Mating Algorithm (EMA). …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…This paper presents an innovative approach using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model optimized by the Barnacles Mating Optimizer (BMO). …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…To overcome these limitations, this research proposes the CNN-LSTM-SA method, an enhanced deep learning approach that integrates Convolutional Neural Networks, Long Short-Term Memory networks, and Self-Attention mechanisms. …”
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Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network by Wen, Dong, Li, Rou, Tang, Hao, Liu, Yijun, Wan, Xianglong, Dong, Xianling, Saripan, M. Iqbal, Lan, Xifa, Song, Haiqing, Zhou, Yanhong

“…Besides, the multi-dimensional conditional mutual information method was used to extract the frequency band features of the EEG data. …”
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Maximizing deep learning-based energy efficiency in 5G downlink MIMO-NOMA systems by using MLP-CNN. by Audah, Kamil, Hussein, Walaa, Noordin, Nor Kamariah, Sali, Aduwati, A.Rasid, Mohd Fadlee

“…It can be utilized with multiple convolutional and hidden layers, trained using specific algorithms to solve power allocation problems. …”
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A joint Bayesian optimization for the classification of fine spatial resolution remotely sensed imagery using object-based convolutional neural networks by Azeez, Omer Saud, M. Shafri, Helmi Z., Alias, Aidi Hizami, Haron, Nuzul Azam

“…A Bayesian technique was used to find the best parameters for the multiresolution segmentation (MRS) algorithm while the CNN model learns the image features at different layers, achieving joint optimization. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…The third proposed segmentation algorithm involves two pipelines for feature extraction: split & merge methods and Contextual Encoding Network (EncNet) with an attention mechanism. …”
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Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques by Salami, Momoh Jimoh Emiyoka, Sidek, Shahrul Na'im

“…An improved method that is based of the combination of Gardner transformation, optimal compensation deconvolution, and signal modelling techniques is suggested in this paper. …”
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Analysis Of Personal Protective Equipment Classification Method Using Deep Learning by Siti Zahrah Nur Ain, Silopung

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Optimizing Hyperparameters for Improved Melanoma Classification using Metaheuristic Algorithm by Adamu, S., Alhussian, H., Aziz, N., Abdulkadir, S.J., Alwadin, A., Imam, A.A., Garba, A., Saidu, Y.

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A sequential handwriting recognition model based on a dynamically configurable CRNN by Al-Saffar, Ahmed, Suryanti, Awang, Al-Saiagh, Wafaa, Al-Khaleefa, Ahmed Salih, Abed, Saad Adnan

“…The proposed DC-CRNN is based on the Salp Swarm Optimization Algorithm (SSA), which generates the optimal structure and hyperparameters for Convolutional Recurrent Neural Networks (CRNNs). …”
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Efficient region of interest based metric learning for effective open world deep face by Faizabadi, Ahmed Rimaz, Mohd Zaki, Hasan Firdaus, Zainal Abidin, Zulkifli, Nik Hashim, Nik Nur Wahidah, Husman, Muhammad Afif

“…The widespread use is due to improvements in deep convolutional neural networks (CNN) and large datasets. …”
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