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ReSTiNet: An efficient deep learning approach to improve human detection accuracy by Shahriar Shakir, Sumi, Dayang Rohaya, Awang Rambli, Mirjalili, Seyedali, Miah, M. Saef Ullah, Muhammad Mudassir, Ejaz

“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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ReSTiNet : An efficient deep learning approach to improve human detection accuracy by Sumit, Shahriar Shakir, Dayang Rohaya, Awang Rambli, Seyedali, Mirjalili, Miah, Md Saef Ullah, Muhammad Mudassir, Ejaz

“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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Framework development in extracting rules from trained neural network / Shuzlina Abdul Rahman, Azlinah Hj Mohamed and Marina Yusoff by Abdul Rahman, Shuzlina, Mohamed (Hj), Azlinah, Yusoff, Marina

“…In addressing this framework, the criteria of each approaches has been explored and analyzed from eight factors: process extraction, merit, demerit, rule type, type of data, rule quality, processing complexity, and the description of each RE technique. The analysis is derived by excavating literature on RE techniques starting from the year 1993 until 2003 focused on supervised learning algorithm. …”
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ReSTiNet: An Efficient Deep Learning Approach to Improve Human Detection Accuracy by Sumit, S.S., Rambli, D.R.A., Mirjalili, S., Miah, M.S.U., Ejaz, M.M.

“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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Improving Patient Rehabilitation Performance In Exercise Games Using Collaborative Filtering Approach by Waidah Ismail, Ismail Ahmed Al-Qasem Al-Hadi, Crina Grosan, Rimuljo Hendradi

Deep learning in public health: Comparative predictive models for COVID-19 case forecasting by Muhammad Usman Tariq, Muhammad Usman Tariq, Ismail, Shuhaida

“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…Grey Wolf Optimizer (GWO) is a recently developed meta-heuristic algorithm which is appealing to researcher owing to its demonstrated performance as cited in the scientific literature. …”
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Analysing the accuracy of machine learning techniques to develop an integrated influent time series model: case study of a sewage treatment plant, Malaysia by Ansari, Mozafar, Othman, Faridah, Abunama, Taher, El-Shafie, Ahmed

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Postsurgery classification of best-corrected visual acuity changes based on Pterygium Characteristics using the Machine Learning Technique by Jais, Fatin Nabihah, Che Azemin, Mohd Zulfaezal, Hilmi, Mohd Radzi, Mohd Tamrin, Mohd Izzuddin, Mohd. Kamal, Khairidzan

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A cognitive mapping approach in real-time haptic rendering interaction for improved spatial learning ability among autistic people / Kesavan Krishnan by Kesavan , Krishnan

“…The constructed framework was evaluated by expert reviews from the perspective of different scholars and re-designed based on the expert reviews. Furthermore, a HBVE application was developed to demonstrate the logical view of the proposed framework. …”
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ReSTiNet : On improving the performance of Tiny-YOLO-Based CNN architecture for applications in human detection by Sumit, Shahriar Shakir, Awang Rambli, Dayang Rohaya, Mirjalili, Seyedali, Ejaz, Muhammad Mudassir, Miah, Md Saef Ullah

“…Human detection technologies have advanced significantly in recent years due to the rapid development of deep learning techniques. Despite recent advances, we still need to adopt the best network-design practices that enable compact sizes, deep designs, and fast training times while maintaining high accuracies. …”
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Applying case reuse and Rule-Based Reasoning (RBR) in object-oriented application framework documentation: Analysis and design by Jani H.M., Lee S.P.

Application of deep learning technique to predict downhole pressure differential in eccentric annulus of ultra-deep well by Krishna, S., Ridha, S., Ilyas, S.U., Campbell, S., Bhan, U., Bataee, M.

“…The data generated from this model, field data, and experimental data are used to train and test the FFBP-DNN networks. The network is developed used Kerasâ��s deep learning framework. After testing the models, the most optimal arrangement of FFBP-DNN is the ReLU algorithm as an activation function, 4-hidden layers, the learning rate of 0.003, and 2300 of training numbers. …”
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Comparative Analysis of Pneumonia Detection from Chest X-Ray Images Using CNN And Transfer Learning by Naveen Kumar, M., Ushasree, ., Che Fuzlina, Fuad

“…Keywords: Pneumonia, Chest X-ray, Deep Learning, Convolutional Neural Network (CNN), Mobile Net, VCG, ReLU, Max pooling.…”
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A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit... by Dokala Janandra, Krishna Kishore

“…Hence, to optimize the cost of integrating RES‘s through newly developed maximum power point tracking (MPPT) based optimization method such as grasshopper optimization algorithm (GOA) has been introduced. …”
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Tool wear prediction models during end milling of glass fibre-reinforced polymer composites by Azwan Iskandar, Azmi, Lin, Richard J.T., Bhattacharyya, Debes

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Customer behavior analysis based on purchasing history and reviews using automated decision-making systems by Allur, Naga Sushma, Deevi, Durga Praveen, Dondapati, Koteswararao, Chetlapalli, Himabindu, Kodadi, Sharadha, Perumal, Thinagaran

“…Machine Learning Techniques for Customer Behavior Analysis: Customer satisfaction can be identified for online purchasing using the machine learning method. …”
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Hospital readmission risk prediction of COVID-19 patients using machine learning / Loo Wei Kit by Loo , Wei Kit

“…Ultimately, a novel Slime Mold Algorithm (SMA) integrated hybrid predictive model was developed. …”
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Artificial intelligence in sustainability reporting / Prof. Dr Corina Joseph by Joseph, Corina

“…One of these definitions describes AI as the utilization of automated algorithms, robotics, or machines that mimic human cognitive functions, enabling them to perform tasks such as learning, identifying, analyzing, and problem-solving (Graham et al., 2020). …”
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