Advancements and Challenges in Character Recognition: A Comparative Analysis of CNN and Deep Learning Approaches by Yang Ximin

“…This paper provides a comprehensive review of character recognition technologies, focusing on the application of Convolutional Neural Networks (CNN) and deep learning methodologies. …”
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Prevention and Detection Research of Intelligent Sports Rehabilitation under the Background of Artificial Intelligence by Qiong Huang, Fubin Wang

“…This paper is aimed at studying the prevention and detection of sports rehabilitation in the context of artificial intelligence and proposing a compliance control method for lower limb rehabilitation robots based on artificial neural networks. In this paper, a double closed-loop control system is designed: the outer loop is an adaptive impedance control model based on sEMG feedback, and the purpose is to adjust the predicted desired joint trajectories. …”
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Performance Prediction of Building Integrated Photovoltaic System Using Hybrid Deep Learning Algorithm by Manivannan Ragupathi, Rengaraj Ramasubbu

“…The suggested multitask learning approach is implemented using LSTM neural networks and evaluated over a range of horizons. …”
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Prediction of Surface Roughness in End Milling Process Using Intelligent Systems: A Comparative Study by Abdel Badie Sharkawy

“…They are (i) radial basis function neural networks (RBFNs), (ii) adaptive neurofuzzy inference systems (ANFISs), and (iii) genetically evolved fuzzy inference systems (G-FISs). …”
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A Closest Resemblance Classifier with Feature Interval Learning and Outranking Measures for Improved Performance by Nabil Belacel

“…We evaluate our classifiers on multiple UCI repository datasets and compare them with established methods, including k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), Random Forest (RF), Neural Networks (NNs), Naive Bayes (NB), and Nearest Centroid (NC). …”
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Pediatric Multiple Sclerosis and Cognition: A Review of Clinical, Neuropsychologic, and Neuroradiologic Features by Ozgul Ekmekci

“…A young age at disease onset is the strongest risk factor for these impairments, which may be due to the effect of inflammatory demyelination and neurodegeneration on the developing central nervous system and neural networks in children. Cognitive impairment has long-term effects on patients’ academic life and the quality of their social life. …”
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Advancements in Image Classification: From Machine Learning to Deep Learning by Cheng Haoran

“…These methods achieve image classification through two stages: feature extraction and classification, but they encounter limitations when confronted with large-scale datasets and complicated tasks. Convolutional Neural Networks (CNNs) have gradually replaced traditional methods in image classification due to the rise of deep learning, resulting in improved accuracy and robustness. …”
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Swarming Computational Procedures for the Coronavirus-Based Mathematical SEIR-NDC Model by Suthep Suantai, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Watcharaporn Cholamjiak

“…The numerical solutions of the SEIR-NDC model are presented by using the computational framework of artificial neural networks (ANNs) together with the swarming optimization procedures aided with the sequential quadratic programming. …”
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Analysis of The Role of Deep Learning Models in Image Classification Applications by Li Xiang

“…The integration of deep learning models, particularly Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs), has revolutionized this process, enabling the development of automated, fast, and practical systems. …”
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Fast Visual Tracking with Enhanced and Gradient-Guide Network by Dun Cao, Renhua Dai

“…The existing Siamese trackers express visual tracking through the cross-correlation operation between two neural networks. Although they dominated the tracking field, their adopted pattern caused two main problems. …”
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The Case of the Disappearing Spindle Burst by Alexandre Tiriac, Mark S. Blumberg

“…., by retinal waves); accordingly, spindle bursts are thought to organize neural networks in the developing brain and establish functional links with the sensory periphery. …”
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Network traffic monitoring based on CNN-SVM by Wu Qian

“…The proposed hybrid model in this study uses convolutional neural networks (CNNs) and support vector machines (SVMs) to address these concerns and increase the effectiveness of network traffic monitoring. …”
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Polariton lattices as binarized neuromorphic networks by Evgeny Sedov, Alexey Kavokin

“…The binary neuron switching mechanism, driven by the nonlinear repulsion through the excitonic component of polaritons, offers computational efficiency and scalability advantages over continuous weight neural networks. Our network enables parallel processing, enhancing computational speed compared to sequential or pulse-coded binary systems. …”
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Optimization Design of Phononic Crystals Based on BPNN-MPA in Applied Mathematical Analysis by Peiyun Ge

“…Therefore, this study combines back propagation neural networks with ocean predator algorithms to optimize the geometric structure of phononic crystals. …”
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CODE-ACCORD: A Corpus of building regulatory data for rule generation towards automatic compliance checking by Hansi Hettiarachchi, Amna Dridi, Mohamed Medhat Gaber, Pouyan Parsafard, Nicoleta Bocaneala, Katja Breitenfelder, Gonçal Costa, Maria Hedblom, Mihaela Juganaru-Mathieu, Thamer Mecharnia, Sumee Park, He Tan, Abdel-Rahman H. Tawil, Edlira Vakaj

“…It enables applying recent trends, such as deep neural networks and large language models, to ACC.…”
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Artificial intelligence (AI) or augmented intelligence? How big data and AI are transforming healthcare: Challenges and opportunities by K Moodley

“…Databases of unimaginable magnitude can be harnessed to develop algorithms for AI and to refine machine learning. Complex neural networks now lie at the core of ubiquitous AI systems in healthcare. …”
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DS-SwinUNet: Redesigning Skip Connection With Double Scale Attention for Land Cover Semantic Segmentation by Zirui Shen, Wanjie Liu, Sheng Xu

“…In recent years, the development of visual transformer has gradually replaced convolutional neural networks in the visual domain with attention computation, causing pure transformer networks to become a trend. …”
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Delaying Onset of Dementia: Are Two Languages Enough? by Morris Freedman, Suvarna Alladi, Howard Chertkow, Ellen Bialystok, Fergus I. M. Craik, Natalie A. Phillips, Vasanta Duggirala, Surampudi Bapi Raju, Thomas H. Bak

“…In the case of bilingualism, cognitive reserve may involve reorganization and strengthening of neural networks that enhance executive control. We review evidence for protective effects of bilingualism from a multicultural perspective involving studies in Toronto and Montreal, Canada, and Hyderabad, India. …”
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Applying MLP-Mixer and gMLP to Human Activity Recognition by Takeru Miyoshi, Makoto Koshino, Hidetaka Nambo

“…The development of deep learning has led to the proposal of various models for human activity recognition (HAR). Convolutional neural networks (CNNs), initially proposed for computer vision tasks, are examples of models applied to sensor data. …”
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A systematic assessment of sentiment analysis models on iraqi dialect-based texts by Hafedh Hameed Hussein, Amir Lakizadeh

“…This study proposes hybrid models combining Convolutional Neural Networks with Long Short-Term Memory called as CNN-LSTM, CNN with Gated Recurrent Unit called as CNN-GRU. and AraBERT, a deep transformer model, to enhance Iraqi sentiment analysis. …”
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