Results 1 to 10 of about 8,378,989 (251)

Vectorial Image Representation for Image Classification [PDF]

open access: yesJournal of Imaging
This paper proposes the transformation S→C→, where S is a digital gray-level image and C→ is a vector expressed through the textural space. The proposed transformation is denominated Vectorial Image Representation on the Texture Space (VIR-TS), given ...
Maria-Eugenia Sánchez-Morales   +5 more
doaj   +4 more sources

An improved novel quantum image representation and its experimental test on IBM quantum experience. [PDF]

open access: yesSci Rep, 2021
Quantum image representation (QIR) is a necessary part of quantum image processing (QIP) and plays an important role in quantum information processing.
Su J, Guo X, Liu C, Lu S, Li L.
europepmc   +2 more sources

Perceptual Image Representation

open access: yesEURASIP Journal on Image and Video Processing, 2007
This paper describes a rarity-based visual attention model working on both still images and video sequences. Applications of this kind of models are numerous and we focus on a perceptual image representation which enhances the perceptually important ...
Matei Mancas   +2 more
doaj   +3 more sources

Digital Image Representation by Atomic Functions: The Compression and Protection of Data for Edge Computing in IoT Systems [PDF]

open access: yesSensors, 2022
Digital images are used in various technological, financial, economic, and social processes. Huge datasets of high-resolution images require protected storage and low resource-intensive processing, especially when applying edge computing (EC) for ...
Viktor Makarichev   +3 more
doaj   +2 more sources

Computer-aided detection and visualization of pulmonary embolism using a novel, compact, and discriminative image representation. [PDF]

open access: yesMed Image Anal, 2019
Diagnosing pulmonary embolism (PE) and excluding disorders that may clinically and radiologically simulate PE poses a challenging task for both human and machine perception.
Tajbakhsh N   +3 more
europepmc   +2 more sources

Image Representation Method Based on Relative Layer Entropy for Insulator Recognition [PDF]

open access: yesEntropy, 2020
Deep convolutional neural networks (DCNNs) with alternating convolutional, pooling and decimation layers are widely used in computer vision, yet current works tend to focus on deeper networks with many layers and neurons, resulting in a high ...
Zhenbing Zhao   +6 more
doaj   +2 more sources

Hypernetwork Functional Image Representation

open access: yesInternational Conference on Artificial Neural Networks, 2019
Motivated by the human way of memorizing images we introduce their functional representation, where an image is represented by a neural network. For this purpose, we construct a hypernetwork which takes an image and returns weights to the target network, which maps point from the plane (representing positions of the pixel) into its corresponding color ...
Sylwester Klocek   +5 more
openaire   +4 more sources

Indoor Image Representation by High-Level Semantic Features [PDF]

open access: goldIEEE Access, 2019
Indoor image features extraction is a fundamental problem in multiple fields such as image processing, pattern recognition, robotics, and so on. Nevertheless, most of the existing feature extraction methods, which extract features based on pixels, color,
Chiranjibi Sitaula   +4 more
doaj   +2 more sources

Interpreting CLIP's Image Representation via Text-Based Decomposition [PDF]

open access: yesInternational Conference on Learning Representations, 2023
We investigate the CLIP image encoder by analyzing how individual model components affect the final representation. We decompose the image representation as a sum across individual image patches, model layers, and attention heads, and use CLIP's text ...
Yossi Gandelsman   +2 more
semanticscholar   +1 more source

Fine-Tuning and training of densenet for histopathology image representation using TCGA diagnostic slides [PDF]

open access: yesMedical Image Anal., 2021
Feature vectors provided by pre-trained deep artificial neural networks have become a dominant source for image representation in recent literature. Their contribution to the performance of image analysis can be improved through fine-tuning.
Abtin Riasatian   +21 more
semanticscholar   +1 more source

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