A novel spectral transformation technique based on special functions for improved chest X-ray image classification. by Abeer Aljohani

“…All our simulation is performed in computation softwares, Matlab and Python. The image pre processing and spectral moments generation is performed in Matlab and the implementation of the classifiers is performed with python. …”
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Sparse Aperture Inverse Synthetic Aperture Radar Imaging for Maneuvering Targets With Migration Through Resolution Cells Correction by Jiaxing Yang, Yong Wang

“…Due to the nonstationarity of the echo, it is hard to form a well-focused sparse aperture inverse synthetic aperture radar (SA-ISAR) image for maneuvering targets by traditional algorithms. …”
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Induction of Convolutional Decision Trees for Semantic Segmentation of Color Images Using Differential Evolution and Time and Memory Reduction Techniques by Adriana-Laura López-Lobato, Héctor-Gabriel Acosta-Mesa, Efrén Mezura-Montes

“…This paper proposes a generalization of the induction process of a CDT with the DE algorithm using color images, implementing two techniques to reduce the computational time and memory employed in the induction process: the median selection technique and a memory of previously evaluated solutions. …”
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A NOVEL DEEP LEARNING APPROACHES FOR MULTI-CLASS HISTOPATHOLOGICAL SUB-IMAGE CLASSIFICATION USING PRIOR KNOWLEDGE by Riyam Ali Yassin, Morteza Valizadeh, Alaa Hussein Abdulaal

“…Convolutional neural networks (CNNs) have shown significant promise in medical image analysis, aiding in the detection of cancer cells and the classification of histopathological images through advanced data processing techniques. …”
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Dual imaging technique for a real-time inspection system of foreign object detection in fresh-cut vegetables by Hary Kurniawan, Muhammad Akbar Andi Arief, Santosh Lohumi, Moon S. Kim, Insuck Baek, Byoung-Kwan Cho

“…Using simple image processing algorithms, FMs could be detected and depicted in two different image windows. …”
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Acute ischemic stroke lesion segmentation in non-contrast CT images using 3D convolutional neural networks by A.V. Dobshik, S.K. Verbitskiy, I.A. Pestunov, K.M. Sherman, Yu.N. Sinyavskiy, A.A. Tulupov, V.B. Berikov

“…In this paper, an automatic algorithm aimed at volumetric segmentation of acute ischemic stroke lesion in non-contrast computed tomography brain 3D images is proposed. …”
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Study on Mesoscopic Damage Evolution Characteristics of Single Joint Sandstone Based on Micro-CT Image and Fractal Theory by Hao Liu, Lulin Zheng, Yujun Zuo, Zhonghu Wu, Wenjibin Sun, Lujing Zheng, Chao Pan, Jianyun Lin, Zehua Zhu, Zhibin Hao

“…This study utilizes DIP (digital image processing) technology for characterizing the mesostructure of sandstone and combines DIP technology with RFPA2D. …”
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A novel approach for encryption and decryption of digital imaging and communications using mathematical modelling in internet of medical things by S. Thalapathiraj, J. Arunnehru, V. C. Bharathi, R. Dhanasekar, L. Vijayaraja, R. Kannadasan, Muhammad Faheem, Arfat Ahmad Khan

“…Abstract This research introduces an innovative algorithm for the encryption and decryption of greyscale digital imaging and communications in medicine images utilizing Laplace transforms. …”
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HENCE: Hardware End-to-End Neural Conditional Entropy Encoder for Lossless 3D Medical Image Compression by Jietao Chen, Qianhao Chen, Huan Zhang, Weijie Chen, Wei Luo, Feng Yu

“…Although using field programmable gate arrays (FPGAs) is feasible to mitigate this disadvantage, existing FPGA-based compression frameworks still need CPU for co-processing. In this work, we propose a hardware end-to-end neural conditional entropy encoder (HENCE), for losslessly compressing 3D medical images with the balanced compression ratio and speed. …”
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Assessing the deep learning based image quality enhancements for the BGO based GE omni legend PET/CT by Meysam Dadgar, Amaryllis Verstraete, Jens Maebe, Yves D’Asseler, Stefaan Vandenberghe

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Cardiac Magnetic Resonance Imaging with Myocardial Strain Assessment Correlates with Cardiopulmonary Exercise Testing in Patients with Pectus Excavatum by André Lollert, Tariq Abu-Tair, Tilman Emrich, Karl-Friedrich Kreitner, Alexander Sterlin, Christoph Kampmann, Gundula Staatz

“…In addition to cardiac volumetry, we assessed the strain rates of both ventricles using a feature-tracking algorithm of a piece of commercially available post-processing software. …”
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Revolutionizing climbing perch disease management: AI-Driven solutions for sustainable aquaculture by Kosit Sriputhorn, Rapeepan Pitakaso, Surasak Matitopanum, Peerawat Luesak, Surajet Khonjun, Rungwasun Kraiklang, Chakat Chueadee, Sarayut Gonwirat

“…This system uniquely combines non-population based differential evolution algorithms for optimizing the mix of image augmentation techniques, with population-based algorithms for integrating image segmentation and convolutional neural network (CNN) architectures. …”
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Nondestructive discrimination of advanced clones and cultivars of strawberry using an innovative approach involving image analysis and machine learning by Ewa Ropelewska, Agnieszka Masny

“…As many as 2172 image parameters were extracted from the image of each fruit converted to different color channels R, G, B, L, a, b, X, Y, Z, U, V, and S and textures with the highest discriminative power were selected to develop models using various machine learning algorithms, such as Multilayer Perceptron, MultiClass Classifier, IBk, and LMT, Linear Discriminant, Quadratic SVM, Subspace Discriminant, and Wide Neural Network. …”
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Effect of bit-size reduced half-precision floating-point format on image pixel characterization for AI applications by J. Jean Jenifer Nesam, S. Sankar Ganesh, Sitharthan Ramachandran

“…However, the hardware implementation of these algorithms demands more delay, area, and power. This work proposes a new mantissa bit-size reduced half-precision floating-point format for processing and characterizing image pixels for machine learning algorithms. …”
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Student Engagement Recognition: Comprehensive Analysis Through EEG and Verification by Image Traits Using Deep Learning Techniques by Ajitha Sukumaran, Arun Manoharan

“…The experimental results of the proposed system were verified by analyzing the image traits of the students using the engagement indicator algorithm. …”
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Deep Learning-Based Instance Segmentation of Galloping High-Speed Railway Overhead Contact System Conductors in Video Images by Xiaotong Yao, Huayu Yuan, Shanpeng Zhao, Wei Tian, Dongzhao Han, Xiaoping Li, Feng Wang, Sihua Wang

“…This work expands upon the YOLO11-seg model and introduces an instance segmentation approach for galloping video and image sensor data of OCS conductors. The algorithm, designed for the stripe-like distribution of OCS conductors in the data, employs four-direction Sobel filters to extract edge features in horizontal, vertical, and diagonal orientations. …”
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A Simple and Robust Gray Image Encryption Scheme Using Chaotic Logistic Map and Artificial Neural Network by Adelaïde Nicole Kengnou Telem, Colince Meli Segning, Godpromesse Kenne, Hilaire Bertrand Fotsin

“…In the proposed method, an external secret key is used to derive the initial conditions for the logistic chaotic maps which are employed to generate weights and biases matrices of the multilayer perceptron (MLP). During the learning process with the backpropagation algorithm, ANN determines the weight matrix of the connections. …”
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A Novel One-Dimensional Chaotic System for Image Encryption in Network Transmission Through Base64 Encoding by Linqing Huang, Qingye Huang, Han Chen, Shuting Cai, Xiaoming Xiong, Jian Yang

“…First, a novel one-dimensional discrete chaotic system (1D-LSCM) with complex chaotic behavior is introduced and extensively tested. Second, a new multi-image encryption algorithm based on the proposed 1D-LSCM and base64 encoding is presented. …”
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Feasibility of estimating the percentage of desert pavement using Tasseled Cap Transformation indices extracted from Landsat 8 images by farzaneh Fotouhi Firoozabad, Atefeh jebali

“…The initial process involved performing pre-processing operations on the satellite image, including radiometric and geometric corrections, to prepare it for processing operations. …”
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Application of the U-Net Deep Learning Model for Segmenting Single-Photon Emission Computed Tomography Myocardial Perfusion Images by Ahmad Alenezi, Ali Mayya, Mahdi Alajmi, Wegdan Almutairi, Dana Alaradah, Hamad Alhamad

“…Detection and diagnosis of CAD are complex processes requiring precise and accurate image processing. …”
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