Aware Computing in Spatial Language Understanding Guided by Cognitively Inspired Knowledge Representation by Masao Yokota

“…Mental image directed semantic theory (MIDST) has proposed an omnisensory mental image model and its description language Lmd. …”
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A imagem como instrumento de identidade – A figuração de São Jerónimo no manuscrito Bíblico ANTT, Lorvão 45 by Inês Correia

“…Our discussion focuses on the image of the 'Scribe' that fills the first initial of a 13th century Bible, Ms. …”
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Sampling signals with finite set of apertures by V. I. Guzhov, I. O. Marchenko, E. E. Trubilina, A. A. Trubilin

“…The type of analytical expression differs from those known in the literature on image sampling. The use of an analytical expression for sampling can be used to reconstruct the original image from the image obtained with different sets of apertures. …”
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Spin-orbital conversion of the light field immediately behind an ideal spherical lens by V.V. Kotlyar, A.A. Kovalev, S.S. Stafeev, E.S. Kozlova, M.A. Telegin

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Context aware machine learning techniques for brain tumor classification and detection – A review by Usman Amjad, Asif Raza, Muhammad Fahad, Doaa Farid, Adnan Akhunzada, Muhammad Abubakar, Hira Beenish

“…Specifically, it focuses on multi-modalities of Magnetic Resonance Imaging (MRI) and histopathology, utilizing Convolutional Neural Networks (CNN) for image processing and analysis. …”
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Application of three-dimensional printing in the planning and execution of aortic aneurysm repair by Harshank Patel, Paul Choi, Jennifer C. Ku, Rosemary Vergara, Rafael Malgor, Dhiren Patel, Yong Li

“…Standardization is enhanced by using artificial intelligence (AI) for image pre-processing before 3D printing. These methods address fallacies in centerline image analysis and manual image pre-processing. …”
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Assessment of Anterior Segment Measurements with Swept Source Optical Coherence Tomography before and after Ab Interno Trabeculotomy (Trabectome) Surgery by Handan Akil, Ping Huang, Vikas Chopra, Brian Francis

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Accepting your Body after Cancer (ABC), a group-based online intervention for women treated for breast cancer: study protocol for a feasibility randomised controlled trial by Sarah Byford, Abigail Jones, Shelley Potter, Paul White, Diana Harcourt, Helena Lewis-Smith, Patricia Fairbrother

“…Nonetheless, rigorously evaluated and effective body image interventions are lacking among this group. …”
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Computer Based Correlation of the Texture of P63 Expressed Nuclei with Histological Tumour Grade, in Laryngeal Carcinomas by Konstantinos Ninos, Spiros Kostopoulos, Ioannis Kalatzis, Panagiota Ravazoula, George Sakelaropoulos, George Panayiotakis, George Economou, Dionisis Cavouras

“…Biopsy specimens from laryngeal tumour lesions of 55 patients diagnosed with laryngeal squamous cell carcinomas were immunohistochemically (IHC) stained for P63 expression. Four images were digitized from each patient’s IHC specimens. …”
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L’imaginaire de l’exil chez Kay Boyle by Anne Reynes

“…In the wake of Ezra Pound and William Carlos Williams, she experimented with the image as a way of reaching for a new sense of “locality”. …”
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Applications of Robust Methods in Spatial Analysis by Selvakkadunko Selvaratnam

“…The proposed method can be extended for future works of image analysis which includes 3 dimensional image analysis.…”
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Is the Linear Modeling Technique Good Enough for Optimal Form Design? A Comparison of Quantitative Analysis Models by Yang-Cheng Lin, Chung-Hsing Yeh, Chen-Cheng Wang, Chun-Chun Wei

“…Whether consumers choose a product depends largely on their perception of the product image. A consumer-oriented design approach presented in this paper helps product designers incorporate consumers’ perceptions of product forms in the design process. …”
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Enhanced ResNet-50 for garbage classification: Feature fusion and depth-separable convolutions. by Lingbo Li, Runpu Wang, Miaojie Zou, Fusen Guo, Yuheng Ren

“…To this end, a new garbage image classification model is proposed, with the ResNet-50 network as the core architecture. …”
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Detection and Segmentation of Glioma Tumors Using an Improved Visual Geometry Group (IVGG) Deep Learning Structure by Parameswari Alagarsamy, Vinoth Kumar Kalimuthu, Bhavani Sridharan

“…The features are computed from the glioma brain image dataset images and the normal brain image dataset images and these features are fed into the classification architecture. …”
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Small Object Detection with Multiscale Features by Guo X. Hu, Zhong Yang, Lei Hu, Li Huang, Jia M. Han

“…The existing object detection algorithm based on the deep convolution neural network needs to carry out multilevel convolution and pooling operations to the entire image in order to extract a deep semantic features of the image. …”
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Keratoconus disease classification with multimodel fusion and vision transformer: a pretrained model approach by Shokufeh Yaraghi, Toktam Khatibi

“…Objective Our objective is to develop a novel keratoconus image classification system that leverages multiple pretrained models and a transformer architecture to achieve state-of-the-art performance in detecting keratoconus.Methods and analysis Three pretrained models were used to extract features from the input images. …”
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Computer Vision-Based Patched and Unpatched Pothole Classification Using Machine Learning Approach Optimized by Forensic-Based Investigation Metaheuristic by Nhat-Duc Hoang, Thanh-Canh Huynh, Van-Duc Tran

“…Using two-dimensional images, patched and unpatched potholes may have similar shapes. …”
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Lens Raster as a Source of Distortions in Integral Photography by E. G. Zaytseva, A. A. Kisliuk, T. O. Laryonova, N. N. Dubina

“…Analysis of methods for recording and reproducing a three-dimensional image allows to distinguish two different approaches. …”
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Polarization Möbius strip at the tight focus of a generalized Poincaré beam by V.V. Kotlyar, A.A. Kovalev, A.M. Telegin

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Independent Component Analysis to Detect Clustered Microcalcification Breast Cancers by R. Gallardo-Caballero, C. J. García-Orellana, A. García-Manso, H. M. González-Velasco, M. Macías-Macías

“…Our system achieves an average of 2.55 false positives per image at a sensitivity of 81.8% and 4.45 at a sensitivity of 91.8% in diagnosing the BCRP_CALC_1 subset of DDSM.…”
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