Congestion Management Using an Optimized Deep Convolution Neural Network in Deregulated Environment by Dhanadeepika B., Vanithasri M., Chakravarthi M.

“…This work introduces a CM approach using Deep Convolution Neural Network (DCNN) for minimizing congestion and supporting Independent System Operators (ISOs). …”
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Brain tumour detection from magnetic resonance imaging using convolutional neural networks by Irene Rethemiotaki

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Comparative Analysis of Input Image Characteristics in Convolutional Neural Network-based Signature Detection by M. Adamec, M. Turcanik

“…This research presents an innovative approach to comparing diverse input image formats with the objective of identifying the optimal methodology for detecting specific malware-related signatures using convolutional neural networks (CNN), which have been specifically developed by the authors for this purpose. …”
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Classification of Review Text using Hybrid Convolutional Neural Network and Gated Recurrent Unit Methods by Fiqih Fathor Rachim, Auli Damayanti, Edi Winarko

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An enhanced light weight face liveness detection method using deep convolutional neural network by Swapnil R. Shinde, Anupkumar M. Bongale, Deepak Dharrao, Sudeep D. Thepade

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Classification of Vernacular Landscape Elements and Design Applications Based on Deep Learning Fully Convolutional Neural Networks by Ya Li, Yun Zhang

“…By integrating an advanced convolutional neural network (CNN) architecture, this study demonstrates its practical utility through rigorous experiments. …”
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SACNN‐IDS: A self‐attention convolutional neural network for intrusion detection in industrial internet of things by Mimonah Al Qathrady, Safi Ullah, Mohammed S. Alshehri, Jawad Ahmad, Sultan Almakdi, Samar M. Alqhtani, Muazzam A. Khan, Baraq Ghaleb

“…This paper proposes a self‐attention convolutional neural network (SACNN) architecture for the detection of malicious activity in IIoT networks and an appropriate feature extraction method to extract the most significant features. …”
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Quantized Convolutional Neural Networks Robustness under Perturbation [version 1; peer review: 2 approved] by Guy Kember, Issam Hammad, Jack Langille

“…We focus on addressing this gap in the context of 8-bit quantized convolutional neural networks (CNNs). We study three state-of-the-art CNNs: ResNet-18, VGG-16, and SqueezeNet1_1, and subject their floating point and fixed point forms to various noise regimes with varying intensities. …”
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Enhancing Real-Time Emotion Recognition in Classroom Environments Using Convolutional Neural Networks: A Step Towards Optical Neural Networks for Advanced Data Processing by Nuphar Avital, Idan Egel, Ido Weinstock, Dror Malka

“…The purpose of this work is to identify emotions based on facial expressions using a deep learning model based on a convolutional neural network (CNN), where facial recognition is performed using the Viola–Jones algorithm on a group of students in a learning environment. …”
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Using Convolutional Block Attention Module for Interpreting the Results of Artificial Neural Networks Operation in Handwritten Signature Identification by V. A. Mishchuk

“…This study explores potential application of a Siamese Convolutional Neural Network (SNN) integrated with a Convolutional Block Attention Module (CBAM) in the field of handwritten signature identification. …”
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Diabetic Retinopathy Classification Using Hybrid Color-Based CLAHE and Blood Vessel in Deep Convolution Neural Network by Ammar Jawad Kadhim, Hadi Seyedarabi, Reza Afrouzian, Fadhil Sahib Hasan

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ZooCNN: A Zero-Order Optimized Convolutional Neural Network for Pneumonia Classification Using Chest Radiographs by Saravana Kumar Ganesan, Parthasarathy Velusamy, Santhosh Rajendran, Ranjithkumar Sakthivel, Manikandan Bose, Baskaran Stephen Inbaraj

“…This article presents a Deep Learning model, Zero-Order Optimized Convolutional Neural Network (ZooCNN), a Zero-Order Optimization (Zoo)-based CNN model for classifying CXR images into three classes, Normal Lungs (NL), Bacterial Pneumonia (BP), and Viral Pneumonia (VP); this model utilizes the Adaptive Synthetic Sampling (ADASYN) approach to ensure class balance in the Kaggle CXR Images (Pneumonia) dataset. …”
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Flexible pressure sensors based on weft–knitted fabrics for real–time body signal monitoring applications with integrated tiny convolutional neural networks by Chi Cuong Vu, Tuan Nghia Nguyen

“…Collected signals are processed through an embedded convolutional neural network (CNN) model capable of monitoring bodily conditions and accurately classifying various physiological movements. …”
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Conv1D-LSTM: Autonomous Breast Cancer Detection Using a One-Dimensional Convolutional Neural Network With Long Short-Term Memory by Mitanshi Rastogi, Meenu Vijarania, Neha Goel, Akshat Agrawal, Cresantus N. Biamba, Celestine Iwendi

“…This paper introduces a new method for detecting breast cancer using a one-dimensional convolutional neural network (1D CNN) and long short-term memory (LSTM). …”
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Predicting microbe-disease associations via graph neural network and contrastive learning by Cong Jiang, Cong Jiang, Junxuan Feng, Junxuan Feng, Bingshen Shan, Bingshen Shan, Qiyue Chen, Jian Yang, Jian Yang, Gang Wang, Gang Wang, Xiaogang Peng, Xiaozheng Li, Xiaozheng Li

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Custom YOLO Object Detection Model for COVID-19 Diagnosis by Noor Najah Ali, Aseel Hameed, Asanka G. Perera, Ali Al_Naji

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Beyond Traditional Biometrics: Harnessing Chest X-Ray Features for Robust Person Identification by Farah Hazem, Bennour Akram, Tahar Mekhaznia, Fahad Ghabban, Abdullah Alsaeedi, Bhawna Goyal

“…However, the training of convolutional neural networks (CNNs) requires copious labelled data and is time-consuming. …”
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YOLO: A Competitive Analysis of Modern Object Detection Algorithms for Road Defects Detection Using Drone Images by Amit Hasan Sadhin, Siti Zaiton Mohd Hashim, Hussein Samma, Nurulaqilla Khamis

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Models and methods for analyzing complex networks and social network structures by Ju. P. Perova, V. P. Grigoriev, D. O. Zhukov

“…Of these, convolutional neural networks demonstrated the best results. …”
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CNN for Computer Vision tasks by Р. Ковальчук, О. Польшакова

“…The aim of the study is to analyze contemporary solutions related to convolutional neural networks (CNN) to select an optimal topology that enhances addressing typical computer vision tasks. …”
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