Search Results - (( basic deep learning algorithm ) OR ( using optimization method algorithm ))

Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

“…Deep Neural Network (DNN) is a combination method between two different subfields of Machine Learning application, including the Artificial Neural Network (ANN) and Deep Learning (DL). …”
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Designing an integrated AIOT system for tracking class attendance by Kuak, Xuan Ren

“…For facial recognition, deep metric learning methods which involve face encoding are used, and the system can highly match student faces with relevant confidence level of 0.75 or above. …”
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Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

“…Nowadays there are many related efforts in detecting spliced images, but most of them are either feature-specific or complicated algorithms. Constrained CNN is basically a Deep Learning CNN model with its first layer weights being constrained so that it only extracts splicing manipulation features instead of object features. …”
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Review and bibliometric analysis of AI-driven advancements in healthcare by Wang, Yi Jie, Choo, Wei Chong, Ng, Keng Yap

“…Research shows that "algorithm", "machine learning", "deep learning", "controlled study", "major clinical study" and "healthcare delivery" as well as "decision support systems" are key topics for research. …”
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer by Tehseen Mazhar, Inayatul Haq, Allah Ditta, Syed Agha Hassnain Mohsan, Faisal Rehman, Imran Zafar, Jualang Azlan Gansau, Lucky Poh Wah Goh

“…Moreover, this paper also defined the basic requirements for creating a skin cancer detection application, which revolves around two main issues: the full segmentation image and the tracking of the lesion on the skin using deep learning. …”
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Investigate And Analysis Of Deep Learning And Machine Learning Algorithm For Face Mask Detection System by Muhammad Ezzuddeen, Suratman

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Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

“…The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. …”
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Review of deep convolution neural network in image classification by Al-Saffar, Ahmed Ali Mohammed, Tao, Hai, Mohammed, Ahmed Talab

“…The convolution neural network model trained by the deep learning algorithm has made remarkable achievements in many large-scale identification tasks in the field of computer vision since its introduction. …”
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

“…The proposed deep learning model renders faster without the use of SMOTE. …”
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A Novel Method for Fashion Clothing Image Classification Based on Deep Learning by Yoon Shin, Seong, Jo, Gwanghyun, Wang, Guangxing

“…This paper suggested a deep learning-based image classification technique based on a CNN model and improved convolutional and pooling layers. …”
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A novel neuroscience-inspired architecture: for computer vision applications by Hassan, Marwa Yousif, Khalifa, Othman Omran, Abu Talib, Azhar, Olanrewaju, Rashidah Funke, Hassan Abdalla Hashim, Aisha

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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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A deep learning approach: The impact of sentiment analysis of Bangladeshi workers over the world by Tomal, Md Raihanul Islam, Kader, Tanveer, Kohbalan, Moorthy, Mazlina, Abdul Majid

“…TF-IDF vectorization was used for feature extraction, followed by basic machine learning algorithms such as Decision Tree, Support Vector Machine, and Naive Bayes. …”
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A review on monocular tracking and mapping: from model-based to data-driven methods by Gadipudi, N., Elamvazuthi, I., Izhar, L.I., Tiwari, L., Hebbalaguppe, R., Lu, C.-K., Doss, A.S.A.

“…Astounding results from early methods based on filtering have intrigued the community to extend these algorithms using other forms of techniques like bundle adjustment and deep learning. …”
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Mobile application for sign language learning with real time feedback by Lee, Xiao Xu Alexis

“…Machine learning algorithms using MediaPipe and deep learning will analyse users' hand motions to provide corrections for improving technique. …”
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A new modern scheme for solving fractal–fractional differential equations based on deep feedforward neural network with multiple hidden layer by Admon, Mohd Rashid, Senu, Norazak, Ahmadian, Ali, Majid, Zanariah Abdul, Salahshour, Soheil

“…During the initial stage of the method development, the basic framework on solving FFDEs is designed. To minimize the burden of computational time, the vectorized algorithm is constructed at the next stage for method to be performed efficiently. …”
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Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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Implementation of hashed cryptography algorithm based on cryptography message syntax by Ali, Mohammed Ahnaf

“…The important study in this research is an automated learning system for deep learning to enhance security. …”
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