Opposition-Based White Shark Optimizer for Optimizing Modified EfficientNetV2 in Road Crack Classification by Mohammed Al-Shalabi, Mohammed A. Mahdi, Malik Braik, Mohammed Azmi Al-Betar, Shahanawaj Ahamad, Sawsan A. Saad

“…Maintaining reliable and long-lasting road infrastructure requires accurate identification and management of pavement cracks, as these cracks can significantly weaken asphalt and concrete surfaces over time. Although Convolutional Neural Networks (CNNs) and meta-heuristic algorithms have proven effective in solving real-world problems, their use in low-contrast pavement crack images is worth investigating. …”
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Design of a hybrid AI network circuit for epilepsy detection with 97.5% accuracy and low cost-latency by Liufang Sheng, Xuanxu Chen, Yuejun Zhang, Ke Yan, Junping Chen, Zhikang Chen, Hanyu Shi, Yi Gong

“…Then, the design of the multiply-accumulate circuit was completed using a parallel-style row computation method, and a pipelined convolutional computation circuit was used to accelerate the convolutional computation and reduce the computational overhead and delay. …”
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Classifying sex with volume-matched brain MRI by Matthis Ebel, Martin Domin, Nicola Neumann, Carsten Oliver Schmidt, Martin Lotze, Mario Stanke

“…MRI data was used from two population-based data sets of 3298 mostly older adults from the Study of Health in Pomerania (SHIP) and 399 mostly younger adults from the Human Connectome Project (HCP), respectively. …”
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Enhancing maize LAI estimation accuracy using unmanned aerial vehicle remote sensing and deep learning techniques by Zhen Chen, Weiguang Zhai, Qian Cheng

“…Therefore, this study evaluates the potential of multi-source feature fusion and convolutional neural networks (CNN) in estimating maize LAI. …”
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Empirical Evaluation and Analysis of YOLO Models in Smart Transportation by Lan Anh Nguyen, Manh Dat Tran, Yongseok Son

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Analysis of the most Important Concepts Related to Social Distancing as A Result of COVID-19 Pandemic: A Review by Hiyam Hashem Saeed, Abdulbasit Alazzawia

“…This paper provides the first review of the substantial focus of convolutional neural networks (CNN)-based techniques. …”
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Crowd anomaly estimation and detection: A review by A. Hussein, M.W. Raed, A. Al-Shaikhi, M. Mohandes, B. Liu

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Spatial Prediction of Soil Continuous and Categorical Properties Using Deep Learning Approaches for Tamil Nadu, India by Thamizh Vendan Tarun Kshatriya, Ramalingam Kumaraperumal, Sellaperumal Pazhanivelan, Nivas Raj Moorthi, Dhanaraju Muthumanickam, Kaliaperumal Ragunath, Jagadeeswaran Ramasamy

“…The validation and test results obtained for each of the soil attributes for both the algorithms were most comparable with the DL-MLP algorithm depicting the attributes’ most intricate spatial organization details, compared to the 1D-CNN model. …”
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Comparison of Faster R-CNN and YOLOv5 for Overlapping Objects Recognition by Muhamad Munawar Yusro, Rozniza Ali, Muhammad Suzuri Hitam

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A Deep Learning-Driven CAD for Breast Cancer Detection via Thermograms: A Compact Multi-Architecture Feature Strategy by Omneya Attallah

“…Breast cancer continues to be the most common malignancy among women worldwide, presenting a considerable public health issue. …”
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Synergistic use of SAR satellites with deep learning model interpolation for investigating of active landslides in Cuenca, Ecuador by Mohammad Amin Khalili, Silvio Coda, Domenico Calcaterra, Diego Di Martire

“…Among the most intense geological disasters, landslides frequently occur throughout the world. …”
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Evaluation of Similarity of Image Explanations Produced by SHAP, LIME and Grad-CAM by Vladyslav Yavtukhovskyi, Violeta Tretynyk

“…Introduction. Convolutional neural networks (CNNs) are a subtype of neural networks developed specifically to work with images [1]. …”
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Comprehensive Evaluation of Techniques for Intelligent Chatter Detection in Micro-Milling Processes by Guilherme Serpa Sestito, Wesley Angelino De Souza, Alessandro Roger Rodrigues, Maira Martins Da Silva

“…Frictional and regenerative chatter are the most relevant unstable dynamic conditions in micro-milling. …”
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Image-Based Malicious Network Traffic Detection Framework: Data-Centric Approach by Doo-Seop Choi, Taeguen Kim, Boojoong Kang, Eul Gyu Im

“…We implemented a malicious network traffic detection framework based on Convolutional Neural Network (CNN) with our feature engineering techniques. …”
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Consistency regularization based semi-supervised plant disease recognition by Murat Ilsever, Ipek Baz

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Interpretation and understanding of asphalt crack detection deep learning models using integrated gradient (I.G.) maps by Gihan P. Ruwanpathirana, Sadeep Thilakarathna, Shanaka Kristombu Baduge

“…Convolutional neural networks (CNNs) have gained popularity due to their ease of implementation and enhanced accuracy. …”
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Detection of Cardiovascular Diseases Using Predictive Models Based on Deep Learning Techniques: A Hybrid Neutrosophic AHP-TOPSIS Approach for Model Selection by Julio Barzola-Monteses, Rosangela Caicedo-Quiroz, Franklin Parrales-Bravo, Cristhian Medina-Suarez, Wendy Yanez-Pazmino, David Zabala-Blanco, Maikel Y. Leyva-Vazquez

“…In this work, three different models were proposed and compared: deep neural networks (DNN), convolutional neural networks (CNN), and multilayer perceptron (MLP). …”
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Interpreting CNN models for musical instrument recognition using multi-spectrogram heatmap analysis: a preliminary study by Rujia Chen, Akbar Ghobakhlou, Ajit Narayanan

“…This task poses significant challenges due to the complexity and variability of musical signals.MethodsIn this study, we employed convolutional neural networks (CNNs) to analyze the contributions of various spectrogram representations—STFT, Log-Mel, MFCC, Chroma, Spectral Contrast, and Tonnetz—to the classification of ten different musical instruments. …”
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New Strategies Based on Hierarchical Matrices for Matrix Polynomial Evaluation in Exascale Computing Era by Luisa Carracciuolo, Valeria Mele

“…Historically, improvements in computing platforms were mostly dependent on simultaneous developments in hardware, software, architecture, and algorithms (a process known as co-design), which raised the performance of computational models. …”
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Intelligent Recognition Method for Ferrography Wear Debris Images Using Improved Mask R-CNN Methods by Xiangwen Xiao, Weixuan Zhang, Qing Wang, Yuan Liu, Yishou Wang

“…This study proposed an intelligent recognition method for ferrography wear debris images, leveraging several improved Mask Region-based Convolutional Neural Network (Mask R-CNN) algorithms to quantitatively calculate both the number of debris particles and their coverage areas. …”
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