Weakly Supervised Semantic Segmentation of Mangrove Ecosystem Using Sentinel-1 SAR and Deep Convolutional Neural Networks by Arsalan Ghorbanian, Ardalan Ghorbanian, Seyed Ali Ahmadi, Ali Mohammadzadeh, Amin Naboureh

Subjects: “…Deep convolutional neural network (CNN)…”
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Advancing brain tumor diagnosis: Deep siamese convolutional neural network as a superior model for MRI classification by Gowtham Murugesan, Pavithra Nagendran, Jeyakumar Natarajan

“…Our analysis employed five advanced classification model categories: machine learning classifiers, deep learning‐based pre‐trained models, convolutional neural networks (CNNs), hyperparameter‐tuned deep CNNs, and deep siamese CNNs (DeepSCNNs). …”
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Deep convolutional fuzzy neural networks with stork optimization on chronic cardiovascular disease monitoring for pervasive healthcare services by Nuzaiha Mohamed, Reem Lafi Almutairi, Sayda Abdelrahim, Randa Alharbi, Fahad M. Alhomayani, Amer Alsulami, Salem Alkhalaf

“…This manuscript presents a deep convolutional fuzzy neural networks with stork optimization on cardiovascular disease classification (DCFNN-SOCVDC) technique for PH services. …”
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Herbify: an ensemble deep learning framework integrating convolutional neural networks and vision transformers for precise herb identification by Farhan Sheth, Ishika Chatter, Manvendra Jasra, Gireesh Kumar, Richa Sharma

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A Deep Convolutional Neural Network Model for Lung Disease Detection Using Chest X-Ray Imaging by Samia Dardouri

“…This study proposes an automated system for detecting multiple lung diseases in x-ray and CT scans using a customized convolutional neural network (CNN) alongside pretrained models and an image enhancement approach. …”
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A Novel Three-Dimensional Direction-of-Arrival Estimation Approach Using a Deep Convolutional Neural Network by Constantinos M. Mylonakis, Zaharias D. Zaharis

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DETECTION OF NON-MELANOMA SKIN CANCER BY DEEP CONVOLUTIONAL NEURAL NETWORK AND STOCHASTIC GRADIENT DESCENT OPTIMIZATION ALGORITHM by Premananda Sahu, Srikanta Kumar Mohapatra, Prakash Kumar Sarang, Jayashree Mohanty, Pradeepta Kumar Sarangi

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Enhancing human–robot collaboration with thermal images and deep neural networks: the unique thermal industrial dataset WLRI-HRC and evaluation of convolutional neural networks by S. Süme, K.-M. Ponomarjova, T. M. Wendt, S. J. Rupitsch

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Identifying Bias in Deep Neural Networks Using Image Transforms by Sai Teja Erukude, Akhil Joshi, Lior Shamir

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Recognition of underlying surface using a convolutional neural network on a single-board computer by D. A. Paulenka, V. A. Kovalev, E. V. Snezhko, V. A. Liauchuk, E. I. Pechkovsky

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Segmentation of pores in carbon fiber reinforced polymers using the U-Net convolutional neural network by Miroslav Yosifov, Patrick Weinberger, Bernhard Plank, Bernhard Fröhler, Markus Hoeglinger, Johann Kastner, Christoph Heinzl

“…The proposed workflow is designed to generate efficient segmentation models with reasonable execution time, applicable even for users using consumer-grade GPU systems. First, U-Net, a convolutional neural network, is modified to handle the segmentation of XCT datasets. …”
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ScarpLearn: an automatic scarp height measurement of normal fault scarps using convolutional neural networks by Léa Pousse-Beltran, Theo Lallemand, Laurence Audin, Pierre Lacan, Andres David Nunez-Meneses, Sophie Giffard-Roisin

“…We developed a Bayesian supervised machine learning method using one-dimentional (1D) convolutional neural networks (CNN) trained on a database of simulated topographic profiles across normal fault scarps, called ScarpLearn. …”
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Week-Ahead Water Demand Forecasting Using Convolutional Neural Network on Multi-Channel Wavelet Scalogram by Adithya Ramachandran, Hatem Mousa, Andreas Maier, Siming Bayer

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Remaining Useful Life Prediction of Rolling Bearings Based on Multiscale Convolutional Neural Network with Integrated Dilated Convolution Blocks by Ran Wang, Ruyu Shi, Xiong Hu, Changqing Shen

“…Remaining useful life (RUL) prediction is necessary for guaranteeing machinery’s safe operation. Among deep learning architectures, convolutional neural network (CNN) has shown achievements in RUL prediction because of its strong ability in representation learning. …”
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Temporal fusion strategy for violence detection: utilising convolutional and LSTM neural networks for surveillance videos by Khaled Merit, Mohammed Beladgham, Abdelmalik Taleb-Ahmed

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Residual learning based convolution neural network for improved channel estimation for VehA channel by Sunita Khichar, Yahui Meng, Abhishek Sharma, Muhammad Saadi, Amir Parniarifard, Sushank Chaudhary

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Damage detection in structural health monitoring using hybrid convolution neural network and recurrent neural network by Dung Bui-Ngoc, Hieu Nguyen-Tran, Lan Nguyen-Ngoc, Hoa Tran-Ngoc, Thanh Bui-Tien, Hung Tran-Viet

“…A convolution neural network is used to extract deep features while recurrent neural network is trained to learn the long-term historical dependency in time series data. …”
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Damage Detection in Structural Health Monitoring using Hybrid Convolution Neural Network and Recurrent Neural Network by Thanh Bui-Tien, Dung Bui-Ngoc, Hieu Nguyen-Tran, Lan Nguyen-Ngoc, Hoa Tran-Ngoc, Hung Tran-Viet

“…A convolution neural network is used to extract deep features while recurrent neural network is trained to learn the long-term historical dependency in time series data. …”
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Advancing EEG based stress detection using spiking neural networks and convolutional spiking neural networks by Aaditya Joshi, Paramveer Singh Matharu, Lokesh Malviya, Manoj Kumar, Akshay Jadhav

“…This paper explores the use of Convolutional Spiking Neural Networks (CSNNs) to enhance EEG signal classification. …”
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Enhancing Early Exit Performance With Uncertainty-Aware Training in Convolutional Neural Networks for Image Classification by Thanu Kurian, Somasundaram Thangam

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