Image dehazing based on double branch convolution and detail enhancement by ZHAI Fengwen, ZHU Yutong, JIN Jing

“…First, in the image dehazing module, we designed a double branch convolutional block based on depth-separable convolution and differential convolution and then combined it with the U-Net network, effectively reducing the detail loss in the image dehazing process. …”
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Improved Hierarchical Convolutional Features for Robust Visual Object Tracking by Jinping Sun

“…Second, the features of the last layer and the second pool layer of the convolutional neural network are extracted to realize the target position prediction from coarse to fine. …”
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Models, systems, networks in economics, engineering, nature and society by D.V. Mirosh

“…Data on vibration studies of traction electric motors of diesel locomotives, as well as direct measurements of the current of the studied asynchronous electric motors, were used as material for testing the capabilities and testing of the neural network. …”

Generative Adversarial Network-Based Lightweight High-Dynamic-Range Image Reconstruction Model by Gustavo de Souza Ferreti, Thuanne Paixão, Ana Beatriz Alvarez

“…The proposed model is based on Generative Adversarial Networks and replaces traditional convolutions with depthwise separable convolutions, reducing the number of parameters while maintaining high visual quality and minimizing luminance artifacts. …”
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MPAR-RCNN: a multi-task network for multiple person detection with attribute recognition by S. Raghavendra, S. K. Abhilash, Venu Madhav Nookala, Jayashree Shetty, Praveen Gurunath Bharathi

“…Unlike the traditional Fast Region-based Convolutional Neural Network (R-CNN), which separately manages person detection and attribute classification with a dual-stage network, the MPAR-RCNN architecture optimizes both tasks within a single structure. …”
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RDAU-Net: A U-Shaped Semantic Segmentation Network for Buildings near Rivers and Lakes Based on a Fusion Approach by Yipeng Wang, Dongmei Wang, Teng Xu, Yifan Shi, Wenguang Liang, Yihong Wang, George P. Petropoulos, Yansong Bao

“…To address the above issues, the present study proposes the design of a U-shaped segmentation network of buildings called RDAU-Net that works through extraction and fuses a convolutional neural network and a transformer to segment buildings. …”
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Lightweight GAN-Assisted Class Imbalance Mitigation for Apple Flower Bud Detection by Wenan Yuan, Peng Li

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Optimised Neural Network Model for Wind Turbine DFIG Converter Fault Diagnosis by Ramesh Kumar Behara, Akshay Kumar Saha

“…The proposed methodology integrates VMD with a hybrid convolutional neural network–long short-term memory (CNN-LSTM) architecture to efficiently extract and learn distinctive temporal and spectral properties from three-phase current sources. …”
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Efficient Visual-Aware Fashion Recommendation Using Compressed Node Features and Graph-Based Learning by Umar Subhan Malhi, Junfeng Zhou, Abdur Rasool, Shahbaz Siddeeq

“…In this paper, we present the Visual-aware Graph Convolutional Network (VAGCN). This novel framework helps improve how visual features can be incorporated into graph-based learning systems for fashion item compatibility predictions. …”
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Mapping the Use of Artificial Intelligence–Based Image Analysis for Clinical Decision‐Making in Dentistry: A Scoping Review by Wei Chen, Monisha Dhawan, Jonathan Liu, Damie Ing, Kruti Mehta, Daniel Tran, Daniel Lawrence, Max Ganhewa, Nicola Cirillo

“…Most of the included studies utilized convolutional neural networks (CNNs) on dental radiographs such as orthopantomograms (OPGs) and intraoral radiographs (bitewings and periapicals). …”
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Online Pre-Diagnosis of Multiple Faults in Proton Exchange Membrane Fuel Cells by Convolutional Neural Network Based Bi-Directional Long Short-Term Memory Parallel Model with Atten... by Junyi Chen, Huijun Ran, Ziyang Chen, Trevor Hocksun Kwan, Qinghe Yao

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Development and application of a model for the automatic evaluation and classification of onions (Allium cepa L.) using a Deep Neural Network (DNN) by Piotr Rybacki, Przemysław Przygodziński, Przemysław Łukasz Kowalczewski, Zuzanna Sawinska, Ireneusz Kowalik, Andrzej Osuch, Ewa Osuch

“…One such method is digital image analysis, which, when combined with instrumentation and deep neural networks, can fully automate the process. The main aim of this study was the development of a model for the automatic evaluation and classification of onions using a deep convolutional neural network (CNN) model. …”
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GA-TongueNet: tongue image segmentation network using innovative DiFP and MDi for stable generalization ability by Zhiyu Dong, Le Zhao, Yajun Fan, Haihua Ma, Changle Shao, Yiran Zhang, Peng Li

“…Experimental results show that the accuracy and generalization ability of GA-TongueNet in complex environments are significantly better than various existing semantic segmentation algorithms based on Convolutional Neural Networks (CNN) and Transformer architectures.…”
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Inferring Body Measurements from 2D Images: A Comprehensive Review by Hezha Mohammedkhan, Hein Fleuren, Çíçek Güven, Eric Postma

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An automated platform to detect, assess, and quantify deterioration in concrete structures by Ibrahim Odeh, Behrouz Shafei

“…To move toward reducing inspection time, cost, and human error, the current study developed a deep convolutional neural network model tailored for detecting and quantifying deterioration in concrete structures. …”
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Detection of COVID-19 Using a Pre-trained CNN Model Over Chest X-ray Images by Mohammadreza Behnia, Touba Torabipour, Safieh Siadat

“…In order to detect this disease, deep learning algorithms and machine vision are widely used by computer scientists. Convolutional neural networks (CNN), DenseNet121, Resnet50, and VGG16 were used in this study for the detection of Covid-19 in X-ray images. …”
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GCBRGCN: Integration of ceRNA and RGCN to Identify Gastric Cancer Biomarkers by Peng Zhi, Yue Liu, Chenghui Zhao, Kunlun He

“…To bridge this gap, our study introduces the GC biomarker relation graph convolution neural network (GCBRGCN) model which integrates the competing endogenous RNA (ceRNA) network with GC clinical informations and whole transcriptomics data, leveraging the relational graph convolutional network (RGCN) to predict GC biomarkers. …”
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DroneSilient (drone + resilient): an anti-drone system by Meghna Manoj Nair, Harini Sriraman, Gadiparthy Harika Sai, V. Pattabiraman

“…DroneSilient has an RF sensor that can identify and imitate the threat presented by recognized drones. Convolutional Network, Modified Blooms Algorithm, RFID, and RF Sensor systems are all integrated into the DroneSilient system as part of this methodology combination, which provides a thorough method for identifying and eliminating drone threats. …”
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OpenFungi: A Machine Learning Dataset for Fungal Image Recognition Tasks by Anca Cighir, Roland Bolboacă, Teri Lenard

“…The quality of the dataset is demonstrated by solving a classification problem with a simple convolutional neural network. A thorough experimental analysis was conducted, where six performance metrics were measured in three distinct validation scenarios. …”
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Optimized Digital Watermarking for Robust Information Security in Embedded Systems by Mohcin Mekhfioui, Nabil El Bazi, Oussama Laayati, Amal Satif, Marouan Bouchouirbat, Chaïmaâ Kissi, Tarik Boujiha, Ahmed Chebak

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