A Novel Local Binary Patterns-Based Approach and Proposed CNN Model to Diagnose Breast Cancer by Analyzing Histopathology Images by Mehmet Gul

“…This article proposed two methods, one CNN-based and the other local binary pattern (LBP)-based, to perform the preliminary diagnosis process on breast cancer histopathology images with high performance. …”
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Fractional Impervious Surface Mapping on Multispectral Images With Visible Shadows via a Bundle-Based Sparse Unmixing Model by Yanze Liu, Dacheng Li, Wei Xiong, Qijin Han, Lingling Ma

“…To solve this problem, we propose a combination of endmember bundle extraction based on superpixel segmentation and sparse unmixing for the ISA estimation of multispectral images containing visible shadows (EESS), considering the city district of Taiyuan as an example. …”
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DenseIncepS115: a novel network-level fusion framework for Alzheimer's disease prediction using MRI images by Fatima Rauf, Muhammad Attique Khan, Ghassen Ben Brahim, Wardah Abrar, Areej Alasiry, Mehrez Marzougui, Seob Jeon, Yunyoung Nam

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Dynamic Monitoring of Grain for Green Program at Chaoyang City, Liaoning Province Based on Landsat Images During 1985—2020 by Shuai Yanmin, Huo Ran, Qu Ge, Shao Congying, Tian Yanjun

“…[Methods] We used the C5.0 algorithm with Landsat images from 1985 to 2020 to extract the spatial-temporal distribution information of land cover in the region. …”
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Enhanced unsupervised domain adaptation with iterative pseudo-label refinement for inter-event oil spill segmentation in SAR images by Guangyan Cui, Jianchao Fan, Yarong Zou

“…To solve these issues, an enhanced unsupervised domain adaptation with iterative pseudo-label refinement (EUDA-PLR) approach is proposed for inter-event oil spill SAR image segmentation. Specifically, the freely downloaded and collected Sentinel-1 and ERS-1/2 oil spill historical data are used as source domains, respectively, which are migrated to each new oil spill event with limited training samples based on adversarial training to improve the timeliness and accuracy of processing new oil spill events. …”
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AI-Based Noise-Reduction Filter for Whole-Body Planar Bone Scintigraphy Reliably Improves Low-Count Images by Csaba Csikos, Sándor Barna, Ákos Kovács, Péter Czina, Ádám Budai, Melinda Szoliková, Iván Gábor Nagy, Borbála Husztik, Gábor Kiszler, Ildikó Garai

“…It was also determined whether there was any difference between the lesions seen on the unfiltered and filtered images. For quantitative analysis, an automatic lesion detector (BS-AI annotator) was utilized as a segmentation algorithm. …”
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Introducing a novel 3D Chen-Rössler map for NTRU-based image encryption with OFDM transmission over a noisy channel by Alain F. Djomo, Lee Mariel H. Yepdia, Yannick P. K. Nkandeu, Yannick A. Abanda, Alain Tiedeu

“…The encryption and decryption processes built around the NTRU algorithm are inserted into an orthogonal frequency division multiplexing system (i.e., the crypto-OFDM system) for secure image transmission in a non-secure channel. …”
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Automatic Reading and Reporting Weather Information from Surface Fax Charts for Ships Sailing in Actual Northern Pacific and Atlantic Oceans by Jun Jian, Yingxiang Zhang, Ke Xu, Peter J. Webster

“…This enabled the expansion of an existing auto-response marine forecasting system’s applications toward north Pacific and Atlantic Oceans, thus enhancing decision-making capabilities and response measures for sailing ships at actual sea. The OpenCV image processing method and YOLOv5s/YOLO8vn algorithm were utilized to make template matches and locate warning symbols and weather reports from surface weather charts. …”
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Machine Learning-based Disease Classification in Tomato (Solanum lycopersicum) Plants by Md Towfiqur Rahman, Sudipto Dhar Dipto, Israt Jahan June, Abdul Momin, Muhammad Rashed Al Mamun

“…Conventional manual inspection methods are time-consuming and subjective, resulting in delays in implementing necessary protection measures. Therefore, an image processing technique and machine learning algorithms were used for rapid and robust detection of diseases in tomato plant leaves, aiming to streamline the detection process for chemical application responses. …”
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An Offline Image Auditing System for Legacy Meter Reading Systems in Developing Countries: A Machine Learning Approach by Natasha Nigar, Hafiz Muhammad Faisal, Muhammad Kashif Shahzad, Shahid Islam, Olukayode Oki

“…The experimental results on 5,000 real-world instances show that the proposed approach processes an image in 0.05 seconds with 94% accuracy. …”
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ILR-Net: Low-light image enhancement network based on the combination of iterative learning mechanism and Retinex theory. by Mohan Yin, Jianbai Yang

“…Aiming at the existing image enhancement algorithms tend to overly focus on increasing brightness, while neglecting the enhancement of color and detailed features. …”
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Approach to Enhancing Panoramic Segmentation in Indoor Construction Sites Based on a Perspective Image Segmentation Foundation Model by Juho Han, Sebeen Yoon, Mingyun Kang, Taehoon Kim

“…Panoramic images in indoor construction sites are gaining attention as valuable tools for process monitoring and quality assessment. …”
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Robust Color Image Encryption Scheme Based on RSA via DCT by Using an Advanced Logic Design Approach by Khalid Kadhim Jabbar, Fahmi Ghozzi, Ahmed Fakhfakh

“…The methods and algorithms for masking or encoding images vary from simple spatial-domain methods to frequency-domain methods, which are the most complex and reliable. …”
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FiSC: A Novel Approach for Fitzpatrick Scale-Based Skin Analyzer’s Image Classification by Guillermo Crocker Garcia, Muhammad Numan Khan, Aftab Alam, Josue Obregon, Tamer Abuhmed, Eui-Nam Huh

“…Our method involves modeling image features as a nine-dimensional feature vector, followed by a dimensionality reduction process to identify the most influential features and dominant areas within the feature space, enabling deployment on low-power devices. …”
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End-to-end deep fusion of hyperspectral imaging and computer vision techniques for rapid detection of wheat seed quality by Tingting Zhang, Jing Li, Jinpeng Tong, Yihu Song, Li Wang, Renye Wu, Xuan Wei, Yuanyuan Song, Rensen Zeng

“…Both conventional machine learning algorithms and deep convolutional neural networks (DCNN) were employed to develop discriminative models using independent datasets. …”
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Detection of Flexible Pavement Surface Cracks in Coastal Regions Using Deep Learning and 2D/3D Images by Carlos Sanchez, Feng Wang, Yongsheng Bai, Haitao Gong

“…To efficiently collect and evaluate thousands of lane-miles, automated processes utilizing image-capturing techniques and detection algorithms are applied to perform these tasks. …”
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The Design and Evaluation of a Direction Sensor System Using Color Marker Patterns Onboard Small Fixed-Wing UAVs in a Wireless Relay System by Kanya Hirai, Masazumi Ueba

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The Impact of a Deep Learning Self-Adaptive Colour Restoration Pipeline for Deep Underwater Images in 3D Reconstruction by M. Vlachos, D. Skarlatos, S. Demesticha

“…Evaluation was performed using established feature detection algorithms, such as SIFT and SURF, applied to multiple underwater datasets capturing diverse imaging conditions. …”
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Pathological omics prediction of early and advanced colon cancer based on artificial intelligence model by Zhe Wang, Yang Wu, Yingjie Li, Qingwen Wang, Hongfei Yi, Hongyan Shi, Xinyue Sun, Chengxiang Liu, Kuanyu Wang

“…Abstract Artificial intelligence (AI) models based on pathological slides have great potential to assist pathologists in disease diagnosis and have become an important research direction in the field of medical image analysis. The aim of this study was to develop an AI model based on whole-slide images to predict the stage of colon cancer. …”
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The short video platform recommendation mechanism based on the improved neural network algorithm to the mainstream media by Mengruo Qi

“…This method combines natural language processing and image analysis in deep learning to construct accurate user and video models, deeply explore user interests, and improve the accuracy and effectiveness of recommendation systems for user preferences. …”
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