Multi-Size Image Encryption Algorithm Based on Fractional-Order Cellular Neural Network by Yinghong Cao, Yan Liu, Kaihua Wang, Xianying Xu, Jinshi Lu

“…In this paper, a multi-size image encryption scheme based on an Fractional-Order Cellular Neural Network model is proposed. …”
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RMIS-Net: a fast medical image segmentation network based on multilayer perceptron by Binbin Zhang, Guoliang Xu, Yiying Xing, Nanjie Li, Deguang Li

“…Remarkably, the proposed architecture requires only 0.03 s per image inference while achieving 27× parameter compression, 10× acceleration in inference speed, and 53× reduction in computational complexity compared to conventional approaches, establishing new benchmarks for efficient yet accurate medical image analysis.…”
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ACGNet: An Alternating Conjugate Gradient Optimization-Based Neural Network for SAR Image Despeckling by Xin Mao, Ying Liu, Chenghao Qiu, Cong Lin

“…To address this issue, this article proposes a supervised collaborative denoising method with alternating optimization, which combines the alternating conjugate gradient method with an SAR despeckling network trained on paired noisy-clean simulated SAR data to progressively optimize image quality, thereby effectively reducing noise while preserving more details and texture information in the image. …”
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Needle tracking and segmentation in breast ultrasound imaging based on spatio-temporal memory network by Qiyun Zhang, Jiawei Chen, Jinhong Wang, Haolin Wang, Yi He, Yi He, Bin Li, Zhemin Zhuang, Huancheng Zeng

“…IntroductionUltrasound-guided needle biopsy is a commonly employed technique in modern medicine for obtaining tissue samples, such as those from breast tumors, for pathological analysis. However, it is limited by the low signal-to-noise ratio and the complex background of breast ultrasound imaging. …”
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Analysis and Classification of Distress on Flexible Pavements Using Convolutional Neural Networks: A Case Study in Benin Republic by Crespin Prudence Yabi, Godfree F. Gbehoun, Bio Chéissou Koto Tamou, Eric Alamou, Mohamed Gibigaye, Ehsan Noroozinejad Farsangi

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EfficientNet-B0 outperforms other CNNs in image-based five-class embryo grading: a comparative analysis by Vincent Jaehyun Shim, Hosup Shim, Sangho Roh

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Satellite Image Classification Using a Hybrid Manta Ray Foraging Optimization Neural Network by Amit Kumar Rai, Nirupama Mandal, Krishna Kant Singh, Ivan Izonin

“…The satellite images contain enormous data that can be used in various applications. …”
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Enhancing Brain Tumor Detection Through Custom Convolutional Neural Networks and Interpretability-Driven Analysis by Kavinda Ashan Kulasinghe Wasalamuni Dewage, Raza Hasan, Bacha Rehman, Salman Mahmood

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Deep Learning-Based Multiclass Framework for Real-Time Melasma Severity Classification: Clinical Image Analysis and Model Interpretability Evaluation by Zhang J, Jiang Q, Chen Q, Hu B, Chen L

“…Future work will integrate multimodal data for more comprehensive assessment.Keywords: melasma, deep learning, convolutional neural networks, MASI, clinical decision support…”
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Label credibility correction based on cell morphological differences for cervical cells classification by Wenbo Pang, Yue Qiu, Shu Jin, Huiyan Jiang, Yi Ma

“…Through a similarity comparison between the cluster samples and the statistical feature centers of each class, the label credibility analysis is carried out to group labels. Finally, a cervical cell images multi-class network is trained using synergistic grouping method. …”
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ANALISIS DISKRIMINAN, REGRESI LOGISTIK, NEURAL NETWORK DAN MARS PADA PENGKLASIFIKASIAN DATA by Thomas Pentury

“…The purpose of this research is to apply and compare the discriminant analysis, logistic regression, Neural Network (NN) and Multivariate Adaptive Regression Spline (MARS) at HBAT and IRIS data. …”
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Altered Effective Connectivity of the Attentional Network in Temporal Lobe Epilepsy with EEG Data by Xiaojie Wei, Haojun Yang, Ruochen Dang, Bingliang Hu, Li Feng, Yuanyuan Xie, Quan Wang

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Attention Deficit Hyperactivity Disorder identification: FMRI data analyzed with CNN and seed-based approach by Anika Siamin Oyshi, Mohammad Hasan, Md. Khabir Uddin Ahamed, Md. Sydur Rahman, Md. Mahfuzul Haque, Mahmudul Alam

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Seed purity assessment by means of spectral imaging by G.V. Nesterov, A.V. Guryleva, A.A. Zolotukhina, D.S. Fomin, D.S. Fomin, Y.K. Shashko, A.S. Machikhin

“…In this work, we propose a technique for identifying impurity grains from spectral images using neural networks that is able to analyze a heap of seeds, grouping grains with similar spectral and morphological characteristics and optimizing the main stages of forming a training sample of a neural network model, recording and processing data. …”
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CLASSIFICATION OF ROAD TRAFFIC CONDITIONS BASED ON TEXTURE FEATURES OF TRAFFIC IMAGES USING NEURAL NETWORKS by Teresa PAMUŁA

“…The paper presents a method of classification of road traffic conditions based on the analysis of the content of images of the traffic flow. …”
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Optimizing binary neural network quantization for fixed pattern noise robustness by Francisco Javier Andreo-Oliver, Gines Domenech-Asensi, Jose Angel Diaz-Madrid, Ramon Ruiz-Merino, Juan Zapata-Perez

“…Abstract This work presents a comprehensive analysis of how extreme data quantization and fixed pattern noise (FPN) from CMOS imagers affect the performance of deep neural networks for image recognition tasks. …”
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A New Quantum Circuits of Quantum Convolutional Neural Network for X-Ray Images Classification by Mohammed Yousif, Belal Al-Khateeb, Begonya Garcia-Zapirain

“…A common model for classifying images is the convolutional neural network (CNN), which has the benefit of effectively using data correlation information. …”
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Comprehensive Investigation of Machine Learning and Deep Learning Networks for Identifying Multispecies Tomato Insect Images by Chittathuru Himala Praharsha, Alwin Poulose, Chetan Badgujar

“…This paper explores using Convolutional Neural Networks (CNNs) to classify tomato pest images automatically. …”
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Automatic Detection of Landslide Surface Cracks from UAV Images Using Improved U-Network by Hao Xu, Li Wang, Bao Shu, Qin Zhang, Xinrui Li

“…Subsequently, building upon the U-Net architecture, an improved encoder–decoder semantic segmentation network (IEDSSNet) was proposed to segment surface cracks from the images with complex backgrounds. …”
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Graph analysis of resting state functional brain networks and associations with cognitive outcomes in survivors of pediatric brain tumor by Eric S. Semmel, Vince D. Calhoun, Frank Hillary, Robin Morris, Tricia Z. King

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