Fluorescence images of skin lesions and automated diagnosis using convolutional neural networks by Matheus B. Rocha, Sebastiao Pratavieira, Renan Souza Vieira, Juliana Duarte Geller, Amanda Lima Mutz Stein, Fernanda Sales Soares de Oliveira, Tania R.P. Canuto, Luciana de Paula Vieira, Renan Rossoni, Maria C.S. Santos, Patricia H.L. Frasson, Renato A. Krohling

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Vanilla Convolutional Neural Network is all you Need for Online and Offline Signature Verification by Yilmaz Mustafa Berkay, Öztürk Kağan

“…On the other hand, those models are designed and hand-crafted specializing in the problem, online or offline SV. In this work, we suggest and show on popular datasets that similar and simple convolutional neural network (CNN) models can achieve state-of-the-art results both for offline and online SV problems. …”
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Effective Skin Cancer Diagnosis Through Federated Learning and Deep Convolutional Neural Networks by Mabrook S. Al-Rakhami, Salman A. AlQahtani, Abdulaziz Alawwad

“…However, detecting it can be a challenging task, even for specialized dermatologists. Early detection is crucial for successful treatment, and deep learning techniques, particularly deep convolutional neural networks (DCNNs), have shown tremendous potential in this area. …”
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Deep Content-Dependent 3-D Convolutional Sparse Coding for Hyperspectral Image Denoising by Haitao Yin, Hao Chen

“…Furthermore, by exploiting the lightweight of separable convolution and the adaptability of hypernetwork, we design a separable content-dependent 3D Convolution (SCD-Conv) to carry out CD-CSCNet. …”
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Training Fully Convolutional Neural Networks for Lightweight, Non-Critical Instance Segmentation Applications by Miguel Veganzones, Ana Cisnal, Eusebio de la Fuente, Juan Carlos Fraile

“…We compare two common fully convolutional network (FCN) architectures, U-Net and ResNet, and fine-tune the fittest to improve segmentation results. …”
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Dental bur detection system based on asymmetric double convolution and adaptive feature fusion by HongLing Hou, Ao Yang, Xiangyao Li, Kangkai Zhu, Yandi Zhao, Zhiqiang Wu

“…A Lightweight Asymmetric Dual Convolution module (LADC) was devised to diminish the detrimental effects of extraneous features on the model’s precision, thereby enhancing the feature extraction network. …”
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Efficient Recognition of the Propagated Orbital Angular Momentum Modes in Turbulences With the Convolutional Neural Network by Zikun Wang, Maxime Irene Dedo, Kai Guo, Keya Zhou, Fei Shen, Yongxuan Sun, Shutian Liu, Zhongyi Guo

“…Generally, atmospheric turbulence can distort the helical phase fronts of OAM beams, which presents a critical challenge to the effective recognition of OAM modes. Recently, convolutional neural network (CNN), as a model of deep learning, has been widely applied to machine vision. …”
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System Development for Liquid Chemicals Point Injection Based on Convolutional Neural Network Models by V. S. Semenyuk, E. A. Nikitin

“…When developing the system, they used the U-net-algorithm of convolutional neural networks, as well as data displaying diseases of winter and spring wheat – brown rust and powdery mildew. …”
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PlantNet: Scalable Convolutional Neural Network for Image-Based Plant Disease Detection by Sinha Anupa, Kumaraswamy Balasubramaniam

“…This research presents PlantNet, a novel Convolutional Neural Network (CNN) architecture tailored for accurate identification of plant diseases from images. …”
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Preprocessing-Free Convolutional Neural Network Model for Arrhythmia Classification Using ECG Images by Chotirose Prathom, Ryuhi Fukuda, Yuto Yokoyanagi, Yoshifumi Okada

“…To address these limitations, this research proposes a convolutional neural network (CNN) model for arrhythmia classification that incorporates two specialized modules. …”
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Automatic Potato Crop Beetle Recognition Method Based on Multiscale Asymmetric Convolution Blocks by Jingjun Cao, Xiaoqing Xian, Minghui Qiu, Xin Li, Yajie Wei, Wanxue Liu, Guifen Zhang, Lihua Jiang

“…Specifically, it comprises several multiscale asymmetric convolution blocks, which are designed to extract features at multiple scales, mainly by integrating different-sized asymmetric convolution kernels in parallel. …”
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Automated skin melanoma diagnostics based on mathematical model of artificial convolutional neural network by D. A. Gavrilov, E. I. Zakirov, E. V. Gameeva, V. Yu. Semenov, O. Yu. Aleksandrova

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Enhanced neurological anomaly detection in MRI images using deep convolutional neural networks by Ahmed Mateen Buttar, Zubair Shaheen, Abdu H. Gumaei, Mogeeb A. A. Mosleh, Mogeeb A. A. Mosleh, Indrajeet Gupta, Samah M. Alzanin, Muhammad Azeem Akbar

“…This study introduces a deep learning framework designed to automate neuro-diagnostics, addressing the limitations of current manual interpretation methods, which are often time-consuming and prone to variability.MethodsWe propose a specialized deep convolutional neural network (DCNN) framework aimed at detecting and classifying neurological anomalies in MRI data. …”
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Medical Image Retrieval Based on Ensemble Learning using Convolutional Neural Networks and Vision Transformers by Ahmed Yahya, Dalya Khaled, Waleed Al-Azzawi, Tawfeeq Alghazali, H. Sabah Jabr, R. Madhat Abdulla, M. Kadhim Abbas Al-Maeeni, N. Hussin Alwan, S. Saad Najeeb, Kh. T. Falih

“…One of the most serious challenges that require special attention is the representational quality of the embeddings generated by the retrieval pipelines. …”
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SEM-Net: A Social–Emotional Music Classification Model for Emotion Regulation and Music Literacy in Individuals with Special Needs by Yu-Chi Chou, Shan-Ken Chien, Pen-Chiang Chao, Yuan-Jin Lin, Chih-Yun Chen, Kuang-Kai Yeh, Yen-Chia Peng, Chen-Hao Tsao, Shih-Lun Chen, Kuo-Chen Li

“…SEM-Net employs a convolutional neural network (CNN) architecture composed of 17 meticulously structured layers to capture complex emotional and musical features effectively. …”
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Hybrid transformer and convolution iteratively optimized pyramid network for brain large deformation image registration by Xinxin Cui, Yuee Zhou, Caihong Wei, Guodong Suo, Fengqing Jin, Jianlan Yang

“…To this end, we propose an innovative hybrid Transformer and convolution iteratively optimized pyramid network for large deformation brain image registration. …”
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Blink Detection Using 3D Convolutional Neural Architectures and Analysis of Accumulated Frame Predictions by George Nousias, Konstantinos K. Delibasis, Georgios Labiris

“…The cropped eye regions are organized as three-dimensional (3D) input with the third dimension spanning time of 300 ms. Two different 3D convolutional neural networks are utilized (a simple 3D CNN and 3D ResNet), as well as a 3D autoencoder combined with a classifier coupled to the latent space. …”
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Efficient Packaging Line Object Counting by Cross-Frame Association With Wavelet Convolutions and Trajectory Compensation by Longxuan Wei, Yutao Zhu, Yufeng Li, Ming Qian, Xiang Zuo, Boan Chen, Shiyu Liang, Zhouhan Lin, Junchi Yan

“…Our approach features WT-YOLO for object detection, a Wavelet Transform-based convolutional neural network that leverages the wavelet transform to capture both spatial and frequency domain information. …”
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DMoC-UNet: A Dynamic Mixture-of-Convolution Network for Enhanced Pathological Image Segmentation by Jingwei Zhu, Lining Qin, Zixin Teng, Xiaomin Li, Kuiwu Li, Haoran Chu

“…This paper proposes a novel pathological image segmentation method, DMoC-UNet, which integrates Dynamic Mixture-of-Convolution (DMoC) modules, Haar wavelet downsampling, and Dual Attention Fusion (DAF) modules to enhance multi-scale feature extraction and fine-grained boundary segmentation. …”
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AI-Driven Innovation Using Multimodal and Personalized Adaptive Education for Students With Special Needs by Nesren Farhah, Muhammad Adnan, Ahmed Abdullah Alqarni, M. Irfan Uddin, Theyazn H. H. Aldhyani

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