Multi-stream feature fusion of vision transformer and CNN for precise epileptic seizure detection from EEG signals by Qi Li, Wei Cao, Anyuan Zhang

“…Methods Our study proposes an epilepsy detection model, CMFViT, based on a Multi-Stream Feature Fusion (MSFF) strategy that fuses a Convolutional Neural Network (CNN) with a Vision Transformer (ViT). …”
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Data-Driven Optimized Load Forecasting: An LSTM-Based RNN Approach for Smart Grids by Muhammad Asghar Majeed, Sotdhipong Phichaisawat, Furqan Asghar, Umair Hussan

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Steering-Angle Prediction and Controller Design Based on Improved YOLOv5 for Steering-by-Wire System by Cunliang Ye, Yunlong Wang, Yongfu Wang, Yan Liu

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Supervised machine learning prediction and investigation of nonlinear optical rectification in Ge/Si0.15Ge0.85 asymmetric coupled triangle quantum wells by A. Cherni, N. Yahyaoui, N. Zeiri, M.L. Bouazizi, M.Al. Zahrani

“…The theoretical data set results are subsequently used to train three machine learning (ML) models, such as artificial neural network (ANN-ML), convolutional neural network (CNN-ML), and Decision Tree (DT-ML), to predict the NOR coefficient based on the structural parameters. …”
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More Accurate Constraints for Self-Supervised Learning in Remote Sensing Images-Based Object Detection by Shangdong Zheng, Zebin Wu, Yang Xu, Qian Liu, Zhihui Wei

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A Comparative Study of Image Processing and Machine Learning Methods for Classification of Rail Welding Defects by Mohale Emmanuel Molefe, Jules Raymond Tapamo, Siboniso Sithembiso Vilakazi

“…Defects formed during the thermite welding process of two sections of rails require the welded joints to be inspected for quality, and the most used non-destructive method for inspection is radiography testing. …”
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Field-grown tomato yield estimation using point cloud segmentation with 3D shaping and RGB pictures from a field robot and digital single lens reflex cameras by B. Ambrus, G. Teschner, A.J. Kovács, M. Neményi, L. Helyes, Z. Pék, S. Takács, T. Alahmad, A. Nyéki

“…Field pictures were used for tomato segmentation to determine the ripeness of the crop. A convolution neural network (CNN) model using TensorFlow library was devised for the segmentation of tomato berries along with a small robot, which had a 59.3 % F1 score. …”
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An Evaluation of Variational Autoencoder in Credit Card Anomaly Detection by Faleh Alshameri, Ran Xia

“…In this study, we evaluate the usage of the convolutional network-based VAE model on a credit card transaction dataset. …”
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Prediction of Vanadium Contamination Distribution Pattern Through Remote Sensing Image Fusion and Machine Learning by Zipeng Zhao, Yuman Sun, Weiwei Jia, Jinyan Yang, Fan Wang

“…The 934 nm and 464 nm wavelengths were identified as the most critical spectral bands for predicting soil vanadium contamination. …”
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Adaptive deep SVM for detecting early heart disease among cardiac patients by S. N. Netra, N. N. Srinidhi, E. Naresh

“…Abstract Heart attack is one of the most common heart diseases, which causes more deaths worldwide. …”
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Deep learning-based underwater metal object detection using input image data and corrosion protection of mild steel used in underwater study: A case study: Part A: Deep learning-ba... by Thankappan Sasilatha, Doss Hebciba Mary Suvakeen Amala, Rajendran Susai Santhammal, Časlav Lačnjevac, Gurmeet Singh

“…The segmented images are given to the DWT Extraction to extract the features from those images. And finally the Convolution Neural Network (CNN) is used to classify the images to detect the objects. …”
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Deep learning and wavelet packet transform for fault diagnosis in double circuit transmission lines by Ziad M. Ali, Ehab M. Esmail

“…The approach is evaluated using multiple deep learning architectures, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), and implemented in MATLAB. …”
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3D densely connected CNN with multi-scale receptive fields and hybrid loss for brain tumor segmentation by Fatemehzahra Adib, Maryam Amirmazlaghani, Mohammad Rahmati

“…Abstract Brain tumors, especially gliomas, are among the most common and aggressive types of tumors in the brain. …”
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A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…The core of the model combines temporal convolutional networks (TCNs) and bidirectional gated recurrent units (BiGRUs). …”
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Research on rock fracture evolution prediction model based on Adam-ConvLSTM and transfer learning by Runze Liu, Ziwei Wang, Yanbo Zhang, Xulong Yao, Shaohong Yan, Zhiyuan Chen, Shuai Wang, Hua Li, Qi Wang

“…To address these challenges, this study develops a deep learning model based on an adaptive moment estimation optimized convolutional long short-term memory neural network (Adam-ConvLSTM) to predict the evolution of rock fractures. …”
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Automated histopathological detection and classification of lung cancer with an image pre-processing pipeline and spatial attention with deep neural networks by Tushar Nayak, Nitila Gokulkrishnan, Krishnaraj Chadaga, Niranjana Sampathila, Hilda Mayrose, Swathi K. S.

“…Proposed in this study is a data pre-processing pipeline for the H&E-stained lung biopsy images along with a customized EfficientNetB3-based Convolutional Neural Network employing spatial attention, trained on a public three-class lung cancer histopathological image dataset. …”
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Image-based Artificial Intelligence-driven modelling for blank shape optimisation in sheet metal forming by Haosu Zhou, Haoran Li, Yingxue Zhao, Peter R.N. Childs, Nan Li

“…Nevertheless, existing methods are mostly constrained by fixed shape parameterisation schemes, limiting their flexibility and effectiveness. …”
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Automated interpretation of deep learning-based water quality assessment system for enhanced environmental management decisions by Javed Mallick, Saeed Alqadhi, Majed Alsubih, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…The aim of this study was to carry out a detailed assessment of the water resources in the region, focussing on the most important aspects affecting water quality. The main objectives were to calculate various water quality indices for drinking and irrigation purposes, to develop an automated system using convolutional neural networks (CNN) to predict these indices and to increase the transparency of these models using explainable artificial intelligence (XAI) methods. …”
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Integrated deep learning framework for driver distraction detection and real-time road object recognition in advanced driver assistance systems by Rakesh Salakapuri, Naveen Kumar Navuri, Thrimurthulu Vobbilineni, G. Ravi, Karthik Karmakonda, K. Asish vardhan

“…Abstract Most accidents are a result of distractions while driving and road user’s safety is a global concern. …”
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Extension of the First-Order Recursive Filters Method to Non-Linear Second-Kind Volterra Integral Equations by Rodolphe Heyd

“…A new numerical method for solving Volterra non-linear convolution integral equations (NLCVIEs) of the second kind is presented in this work. …”
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