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Decision-level fusion for single-view gait recognition with various carrying and clothing conditions
Published 2017“…The gait data is firstly processed using three gait representation methods as the features sources; Accumulated Prediction Image (API) and two new gait representations namely; Accumulated Flow Image (AFI) and Edge-Masked Active Energy Image (EMAEI). …”
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Extreme Early Image Recognition Using Event-Based Vision
Published 2023“…<p dir="ltr">While deep learning algorithms have advanced to a great extent, they are all designed for frame-based imagers that capture images at a high frame rate, which leads to a high storage requirement, heavy computations, and very high power consumption. …”
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Competitive learning/reflected residual vector quantization for coding angiogram images
Published 2003“…It was found that it has a higher probability to diverge when used with nonGaussian and nonLaplacian image sources such as angiogram images. By employing competitive learning neural network in the codebook design process, we tried to obtain a stable and convergent algorithm. …”
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Lung cancer medical images classification using hybrid CNN-SVM
Published 2021“…Computer-Aided Detection (CAD) has been used to process CT images of the lung to determine whether an image has traces of cancer. …”
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Large-scale annotation dataset for fetal head biometry in ultrasound images
Published 2023“…It is also compatible with multiple medical imaging software and deep learning frameworks. The reliability of the annotations is verified through a two-step validation process involving a Senior Attending Physician and a Radiologic Technologist. …”
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Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units
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Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…We searched Embase, PubMed, Scopus, and Google Scholar to retrieve relevant studies. After pre-processing and screening, we extracted data from 34 studies that fulfilled the inclusion criteria. …”
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A Novel Encryption Method for Dorsal Hand Vein Images on a Microcomputer
Published 2019“…Second, the pre- and post-processed images were encrypted with a new encryption algorithm in the microcomputer environment. …”
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
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CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…Dysgraphia is a neurological disorder that hinders the acquisition process of normal writing skills in children, resulting in poor writing abilities. …”
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CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…<p dir="ltr">Dysgraphia is a neurological disorder that hinders the acquisition process of normal writing skills in children, resulting in poor writing abilities. …”
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A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method
Published 2022“…The LSB substitution method can minimize the error rate in embedding process and can achieve greater reliability in criteria, using novel algorithm based on value difference. …”
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Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review
Published 2025“…Studies were included if they focused on the application of AI in US imaging for CTS diagnosis. Editorials, expert opinions, conference papers, dataset publications, and studies that did not have a clear clinical application of the AI algorithm were excluded.…”
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Salak Image Classification Method Based Deep Learning Technique Using Two Transfer Learning Models
Published 2022“…Pre-processing on the dataset is required to standardize the dataset by resizing the image into 224 * 224 pixels, convert into jpg format and augmentation. …”
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XBeGene: Scalable XML Documents Generator by Example Based on Real Data
Published 2012“…Inspired by the query-by-example paradigm in information retrieval, Our generator system i)allows the user to provide her own sample XML documents as input, ii) analyzes the structure, occurrence frequencies, and content distributions for each XML element in the user input documents, and iii) produces synthetic XML documents which closely concur, in both structural and content features, to the user's input data. …”
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