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Journal articles on the topic 'Image guide'

Author: Grafiati

Published: 28 April 2023

Last updated: 19 July 2025

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1

Liao, Ronghao, Guangyuan Wu, and Yuheng Wu. "Adaptive window-based multispectral image demosaicking method using pseudo-panchromatic image." Laser Physics Letters 22, no. 4 (2025): 045202. https://doi.org/10.1088/1612-202x/adbd1a.

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Abstract Multispectral image demosaicking is a challenging problem for single-sensor multispectral imaging systems with the multispectral filter array. In this paper, we propose an adaptive window-based multispectral image demosaicking method using a pseudo-panchromatic image (PPI). This method aims to use the spectral correlation between channels to recover the missing pixels in the mosaic image. First, a set of weighted average filters based on adaptive sparse windows is used to generate a PPI from the mosaic image. Then, the guided filtering window is adaptively adjusted according to the di

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Berry, E., M. Cuppone, S. Porada, et al. "Personalised image-based templates for intra-operative guidance." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 219, no. 2 (2005): 111–18. http://dx.doi.org/10.1243/095441105x9273.

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The high rate of unplanned perforation, poor fixation, and nerve injury with freehand pedicle screw insertion has led to the use of image-guided navigation systems. Although these improve accuracy, they have several drawbacks that could be overcome by using image-based drilling guide templates. The accuracy of such templates was tested in a cadaveric study of screw placement in the lumbar, thoracic, and cervical regions of the spine. The dimensional stability with autoclaving of duraform polyamide, to be used for manufacturing the guides, was first determined using test specimens. Computed tom

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Li, Zhan, Jianhang Zhang, Ruibin Zhong, et al. "Lightweight and Efficient Image Dehazing Network Guided by Transmission Estimation from Real-World Hazy Scenes." Sensors 21, no. 3 (2021): 960. http://dx.doi.org/10.3390/s21030960.

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In this paper, a transmission-guided lightweight neural network called TGL-Net is proposed for efficient image dehazing. Unlike most current dehazing methods that produce simulated transmission maps from depth data and haze-free images, in the proposed work, guided transmission maps are computed automatically using a filter-refined dark-channel-prior (F-DCP) method from real-world hazy images as a regularizer, which facilitates network training not only on synthetic data, but also on natural images. A double-error loss function that combines the errors of a transmission map with the errors of

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Ishizaka, Hiroshi. "Directable Needle Guide: Efficacy for Image-Guided Percutaneous Interventions." ISRN Radiology 2013 (November 27, 2013): 1–3. http://dx.doi.org/10.5402/2013/516941.

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Diagnostic and therapeutic image-guided percutaneous interventions have become increasingly important in the clinical management of various conditions. Though precise needle placement via a safe route is essential for successful percutaneous interventions, it is often difficult in cases of deeply situated, small lesions. The present paper describes the efficacy of the directable needle guide (DNG), which allows manipulation of the direction of a fine needle within organs. The DNG was used in patients for needle biopsy of hepatic (n=26) and splenic (n=1) lesions and for percutaneous ethanol inj

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Zhang, Yuan, Peng Wang, Ji Xiang Li, Shi Wei Yin, and Jing Lei Xin. "Path Segmentation Algorithm for Automatic Guided Vehicle Based on Machine Vision." Key Engineering Materials 431-432 (March 2010): 330–33. http://dx.doi.org/10.4028/www.scientific.net/kem.431-432.330.

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A novel path segmentation algorithm for automatic guided vehicle is designed by machine vision technology. Firstly, wiener filter based on parameter estimate is used to restore path image in HIS model. Secondly, mutivariate stepwise fitted regression method is adopted to smooth guide line edge of path image. It can be concluded that path guide line of automatic guided vehicle under industry surrounding may be recognized accurately through this way.

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Chen, Bowei, Li Chen, Umara Khalid, and Shuai Zhang. "IFSrNet: Multi-Scale IFS Feature-Guided Registration Network Using Multispectral Image-to-Image Translation." Electronics 13, no. 12 (2024): 2240. http://dx.doi.org/10.3390/electronics13122240.

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Multispectral image registration is the process of aligning the spatial regions of two images with different distributions. One of the main challenges it faces is to resolve the severe inconsistencies between the reference and target images. This paper presents a novel multispectral image registration network, Multi-scale Intuitionistic Fuzzy Set Feature-guided Registration Network (IFSrNet), to address multispectral image registration. IFSrNet generates pseudo-infrared images from visible images using Cycle Generative Adversarial Network (CycleGAN), which is equipped with a multi-head attenti

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Ji, Jingyu, Yuhua Zhang, Zhilong Lin, et al. "Fusion of Infrared and Visible Images Based on Optimized Low-Rank Matrix Factorization with Guided Filtering." Electronics 11, no. 13 (2022): 2003. http://dx.doi.org/10.3390/electronics11132003.

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In recent years, image fusion has been a research hotspot. However, it is still a big challenge to balance the problems of noiseless image fusion and noisy image fusion. In order to improve the weak performance and low robustness of existing image fusion algorithms in noisy images, an infrared and visible image fusion algorithm based on optimized low-rank matrix factorization with guided filtering is proposed. First, the minimized error reconstruction factorization is introduced into the low-rank matrix, which effectively enhances the optimization performance, and obtains the base image with g

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Karthikesh, Madhumithra S., and Xinmai Yang. "Photoacoustic image-guided interventions." Experimental Biology and Medicine 245, no. 4 (2019): 330–41. http://dx.doi.org/10.1177/1535370219889323.

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Photoacoustic imaging has demonstrated its potential for diagnosis over the last few decades. In recent years, its unique imaging capabilities, such as detecting structural, functional and molecular information in deep regions with optical contrast and ultrasound resolution, have opened up many opportunities for photoacoustic imaging to be used during image-guided interventions. Numerous studies have investigated the capability of photoacoustic imaging to guide various interventions such as drug delivery, therapies, surgeries, and biopsies. These studies have demonstrated that photoacoustic im

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Alam, Muhammad S., Farhan B. Mohamed, and AKM B. Hossain. "Self-Localization of Guide Robots Through Image Classification." Baghdad Science Journal 21, no. 2(SI) (2024): 0832. http://dx.doi.org/10.21123/bsj.2024.9648.

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The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots. To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such

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Gao, Guxue, Huicheng Lai, and Zhenhong Jia. "Unsupervised Image Dedusting via a Cycle-Consistent Generative Adversarial Network." Remote Sensing 15, no. 5 (2023): 1311. http://dx.doi.org/10.3390/rs15051311.

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In sand–dust weather, the quality of the image is seriously degraded, which affects the ability of advanced applications to image using remote sensing. To improve the image quality and enhance the performance of image dedusting, we propose an end-to-end cyclic generative adversarial network (D-CycleGAN) for image dedusting, which does not require pairs of sand–dust images and corresponding ground truth images for training. In other words, we train the network in an unpaired way. Specifically, we designed a jointly optimized guided module (JOGM), comprised of the sandy guided synthesis module (

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Naufal, Faishal Zaka, Muhammad Febrian Rachmadi, and Adila Alfa Krisnadhi. "Astronomical Image Denoising Using AttentionGAN." Syntax Literate ; Jurnal Ilmiah Indonesia 10, no. 1 (2025): 222–35. https://doi.org/10.36418/syntax-literate.v10i1.13154.

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Denoising astronomical images is a significant challenge in the field of astronomical data processing. Image data acquired from astronomical sources typically contains noise from various sources. The study aims to investigate the denoising of astronomical images using an image-to-image translation approach with AttentionGAN method. This method combines attention-guided techniques with a Generative Adversarial Network (GAN) model to improve the quality of noisy astronomical images. Attention-guided technique allows the model to learn the most important features of the image and guide the image

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Chen, Ying, Dihe Huang, Shang Xu, Jianlin Liu, and Yong Liu. "Guide Local Feature Matching by Overlap Estimation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 1 (2022): 365–73. http://dx.doi.org/10.1609/aaai.v36i1.19913.

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Local image feature matching under large appearance, viewpoint, and distance changes is challenging yet important. Conventional methods detect and match tentative local features across the whole images, with heuristic consistency checks to guarantee reliable matches. In this paper, we introduce a novel Overlap Estimation method conditioned on image pairs with TRansformer, named OETR, to constrain local feature matching in the commonly visible region. OETR performs overlap estimation in a two step process of feature correlation and then overlap regression. As a preprocessing module, OETR can be

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Li, Jinfeng. "Low-light image enhancement with contrast regularization." Frontiers in Computing and Intelligent Systems 1, no. 3 (2022): 25–28. http://dx.doi.org/10.54097/fcis.v1i3.2022.

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Because the processing of existing low-light images undergoes multiple sampling processing, there is serious information degradation, and only clear images are used as positive samples to guide network training, low-light image enhancement processing is still a challenging and unsettled problem. Therefore, a multi-scale contrast learning low-light image enhancement network is proposed. First, the image generates rich features through the input module, and then the features are imported into a multi-scale enhancement network with dense residual blocks, using positive and negative samples to gui

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Shin, HyunGyu. "A study on gisaeng appearing in 『Daegyeongseong Guide』 and the Joseon Exhibition in 1929." Korean Society of Gyobang and Culture 3, no. 2 (2022): 9–29. http://dx.doi.org/10.58936/gcr.2023.12.3.2.9.

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This paper attempted to analyze the content and reveal its meaning, focusing on the tourist guide 『Daegyeongseong Guide』 published in 1929 and the gisaeng image that appeared in the Joseon Expo. In particular, the 1929 Guide to Daegyeongseong has many references to the Joseon Expo. The Joseon Expo held at Gyeongbokgung Palace in 1929 was an ambitious project promoted by the Japanese Government-General of Korea to commemorate the 20th anniversary of the city administration. Moreover, among the many performances held at the Joseon Expo, the performance of the Gisaeng Association, or Gwonbeon Gis

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ZHANG, Jiajun, Jing LIAN, Jizhao LIU, Zilong DONG, and Huaikun ZHANG. "Using image smoothing structure information to guide image inpainting." Optics and Precision Engineering 32, no. 4 (2024): 549–64. http://dx.doi.org/10.37188/ope.20243204.0549.

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Safirin Karis, Mohd, Nursabillilah Mohd Ali, Mohd Azamuddin Ali, et al. "Guide Sign Analysis of Traffic Sign Data-Set Using Supervised Spiking Neuron Technique." International Journal of Engineering & Technology 7, no. 3.14 (2018): 221. http://dx.doi.org/10.14419/ijet.v7i3.14.16897.

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In this paper, 20 guided traffic signs mostly displayed around Malacca area were selected as project databased. Early hypothesis was made as the error for each usable image will increased as more interference introduced to the original image used. Three types of conditions which are hidden region, image brightness and image rotation were selected as an experiment to analyze the performance of each sign used. Each condition will perform a specific error to generate their mean value and in the same, image recognition will take place in the matchup process. By focusing on the result, it produces

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17

Ariav, Ido, and Israel Cohen. "Fully Cross-Attention Transformer for Guided Depth Super-Resolution." Sensors 23, no. 5 (2023): 2723. http://dx.doi.org/10.3390/s23052723.

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Modern depth sensors are often characterized by low spatial resolution, which hinders their use in real-world applications. However, the depth map in many scenarios is accompanied by a corresponding high-resolution color image. In light of this, learning-based methods have been extensively used for guided super-resolution of depth maps. A guided super-resolution scheme uses a corresponding high-resolution color image to infer high-resolution depth maps from low-resolution ones. Unfortunately, these methods still have texture copying problems due to improper guidance from color images. Specific

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Wang, Yujia, Fang-Lue Zhang, and Neil A. Dodgson. "Target Scanpath-Guided 360-Degree Image Enhancement." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 8 (2025): 8169–77. https://doi.org/10.1609/aaai.v39i8.32881.

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360° images have wide applications in fields such as virtual reality and user experience design. Our goal is to adjust these images to guide users' visual attention. To achieve this, we present a novel task: target scanpath-guided 360° image enhancement, which aims to enhance 360° images based on user-specified target scanpaths. We develop a Progressive Scanpath-Guided Enhancement Method (PSEM) to address this problem through three stages. In the first stage, we propose a Time-Alignment and Spatial Similarity Clustering (TASSC) algorithm that accounts for the spherical nature of 360° images an

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Aspalli, Pooja, and Prakash Pattan. "Image Registration and Fusion using Moving Frame based Decomposition Framework Algorithm." International Journal of Innovative Technology and Exploring Engineering 10, no. 5 (2021): 57–63. http://dx.doi.org/10.35940/ijitee.e8669.0310521.

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Image fusion is an important process in the medical image diagnostics methods. Fusing images by obtaining information from different source and different types of images(modals) called multi-modal image fusion. This paper implements an effective and fast spatial domain based multimodal image fusion using moving frame based decomposition (MFDF)method. Images from two different modalities are taken and decomposed to texture and approximation components. Weight mapping strategy is applied along with the guide filtering to fuse the approximation components using the final map. Weight mapping using

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Pooja, Aspalli, and Prakash Pattan Dr. "Image Registration and Fusion using Moving Frame based Decomposition Framework Algorithm." International Journal of Innovative Technology and Exploring Engineering (IJITEE) 10, no. 5 (2021): 57–63. https://doi.org/10.35940/ijitee.E8669.0310521.

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Image fusion is an important process in the medical image diagnostics methods. Fusing images by obtaining information from different source and different types of images(modals) called multi-modal image fusion. This paper implements an effective and fast spatial domain based multi-modal image fusion using moving frame based decomposition (MFDF)method. Images from two different modalities are taken and decomposed to texture and approximation components. Weight mapping strategy is applied along with the guide filtering to fuse the approximation components using the final map. Weight mapping usin

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Shi, Yunhui, Liping Ye, Jin Wang, et al. "Syntax-Guided Content-Adaptive Transform for Image Compression." Sensors 24, no. 16 (2024): 5439. http://dx.doi.org/10.3390/s24165439.

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The surge in image data has significantly increased the pressure on storage and transmission, posing new challenges for image compression technology. The structural texture of an image implies its statistical characteristics, which is effective for image encoding and decoding. Consequently, content-adaptive compression methods based on learning can better capture the content attributes of images, thereby enhancing encoding performance. However, learned image compression methods do not comprehensively account for both the global and local correlations among the pixels within an image. Moreover,

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Xie, Xuanyuan, and Jieyu Zhao. "GDUI: Guided Diffusion Model for Unlabeled Images." Algorithms 17, no. 3 (2024): 125. http://dx.doi.org/10.3390/a17030125.

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The diffusion model has made progress in the field of image synthesis, especially in the area of conditional image synthesis. However, this improvement is highly dependent on large annotated datasets. To tackle this challenge, we present the Guided Diffusion model for Unlabeled Images (GDUI) framework in this article. It utilizes the inherent feature similarity and semantic differences in the data, as well as the downstream transferability of Contrastive Language-Image Pretraining (CLIP), to guide the diffusion model in generating high-quality images. We design two semantic-aware algorithms, n

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You, Jane, Qin Li, and Jinghua Wang. "On Hierarchical Content-Based Image Retrieval by Dynamic Indexing and Guided Search." International Journal of Cognitive Informatics and Natural Intelligence 4, no. 4 (2010): 18–36. http://dx.doi.org/10.4018/jcini.2010100102.

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This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing. It also provides an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity

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Li, Yang, Haitao Yang, and Yuge Gao. "An Image Fusion Algorithm Based on Improved RGF and Visual Saliency Map." Emergency Medicine International 2022 (August 25, 2022): 1–10. http://dx.doi.org/10.1155/2022/1693531.

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To solve the artifact problem in fused images and the lack of enough generalization under different scenarios of existing fusion algorithms, the paper proposes an image fusion algorithm based on improved RGF and visual saliency map to realize fusion for infrared and visible light images and a multimode medical image. Firstly, the paper uses RGF (rolling guidance filter) and Gaussian filter to decompose the image into the base layer, interlayer, and detail layer by a different scale. Secondly, the paper obtains a visual weight map by the calculation of the source image and uses the guided filte

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Li, Xinyu, Zhi Qiao, Gang Wan, et al. "Depth-Guided Bilateral Grid Feature Fusion Network for Dehazing." Sensors 24, no. 11 (2024): 3589. http://dx.doi.org/10.3390/s24113589.

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In adverse foggy weather conditions, images captured are adversely affected by natural environmental factors, resulting in reduced image contrast and diminished visibility. Traditional image dehazing methods typically rely on prior knowledge, but their efficacy diminishes in practical, complex environments. Deep learning methods have shown promise in single-image dehazing tasks, but often struggle to fully leverage depth and edge information, leading to blurred edges and incomplete dehazing effects. To address these challenges, this paper proposes a deep-guided bilateral grid feature fusion de

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Bevilaqua, Marcus. "Guide to image editing and production of figures for scientific publications with an emphasis on taxonomy Image editing for scientific publications." Zoosystematics and Evolution 96, no. 1 (2020): 139–58. http://dx.doi.org/10.3897/zse.96.49225.

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Figures for scientific publications go through various stages from the planning, to the capturing of images, to the production of finished figures for publication. This guide is meant to familiarise the reader with the main image-editing software used by professional photographers. The guide’s focus is on digital photo editing and the production of figures using Adobe Photoshop to produce publication-quality figures for scientific publications. This guide will be of fundamental use for the academic public, especially taxonomists and others who work with images. Besides, it should be useful for

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Bevilaqua, Marcus. "Guide to image editing and production of figures for scientific publications with an emphasis on taxonomy Image editing for scientific publications." Zoosystematics and Evolution 96, no. (1) (2020): 139–58. https://doi.org/10.3897/zse.96.49225.

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Figures for scientific publications go through various stages from the planning, to the capturing of images, to the production of finished figures for publication. This guide is meant to familiarise the reader with the main image-editing software used by professional photographers. The guide's focus is on digital photo editing and the production of figures using Adobe Photoshop to produce publication-quality figures for scientific publications. This guide will be of fundamental use for the academic public, especially taxonomists and others who work with images. Besides, it should be useful for

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LAY, YUN-LONG, PEI-WEN CHEN, and HUI-JEN YANG. "THE MACHINE VISION BLIND GUIDE SYSTEM." Biomedical Engineering: Applications, Basis and Communications 14, no. 02 (2002): 81–85. http://dx.doi.org/10.4015/s1016237202000127.

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The available guide tools of the orientation and mobility for a blind are the cane, guide dog and electronic guide devices. A cane is easy to detect the hindrance that is in front of the user but not for the hindrance above the user waist. That's why a cane user of a blind sometimes will be hit by the upper hindrance. Guide dog is a very powerful mobility guider but expensive and the training and living care for the dogs are difficult. Hence, guide dog is not popular in many countries. The electronic devices for blind guide tools such as laser cane; sonic glasses, sonic guide etc. can only det

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Enam, Rabia Noor, Muhammad Tahir, Syed Muhammad Nabeel Mustafa, Rehan Qureshi, and Hasan Shahid. "Tourist Guide via Image Processing Techniques." Pakistan Journal of Engineering and Technology 4, no. 2 (2021): 144–48. http://dx.doi.org/10.51846/vol4iss2pp144-148.

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To achieve the goal of identification, image processing and recognition is performed on the actual picture transformation. The amount of information included in an image is enormous because it is a two-dimensional space. Neural network image recognition is a new type of picture recognition technology developed by modern computer innovation. In this paper we have used neural network to implement image-based location identification. Using the image data, we have evaluated our proposed model’s predictive performance. By including more hidden layers in the convolution neural network, it is feasibl

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Murray, Richard. "What image features guide lightness perception?" Journal of Vision 17, no. 15 (2017): 5. http://dx.doi.org/10.1167/17.15.5a.

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Kim, Minjung, Jason M. Gold, and Richard F. Murray. "What image features guide lightness perception?" Journal of Vision 18, no. 13 (2018): 1. http://dx.doi.org/10.1167/18.13.1.

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Ghaemi, H. F., Yao Li, Tineke Thio, and T. Wang. "Fiber image guide with subwavelength resolution." Applied Physics Letters 72, no. 10 (1998): 1137–39. http://dx.doi.org/10.1063/1.120994.

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Lavin, Michael R. "A librarian's guide to Image Comics." Serials Review 24, no. 2 (1998): 79–92. http://dx.doi.org/10.1080/00987913.1998.10764447.

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Evans, D., and J. Romer. "A Guide to Guernsey image rights." Journal of Intellectual Property Law & Practice 8, no. 10 (2013): 761–63. http://dx.doi.org/10.1093/jiplp/jpt153.

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Earle, Greville. "A user's guide to image processing." Physics World 5, no. 8 (1992): 31–36. http://dx.doi.org/10.1088/2058-7058/5/8/30.

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Tiwari, A. K., and R. P. Singh. "An efficient image guide mode launcher." International Journal of Infrared and Millimeter Waves 7, no. 6 (1986): 845–56. http://dx.doi.org/10.1007/bf01013031.

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Zou, Huanxin, Shitian He, Xu Cao, et al. "Rescaling-Assisted Super-Resolution for Medium-Low Resolution Remote Sensing Ship Detection." Remote Sensing 14, no. 11 (2022): 2566. http://dx.doi.org/10.3390/rs14112566.

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Medium-low resolution (M-LR) remote sensing ship detection is a challenging problem due to the small target sizes and insufficient appearance information. Although image super resolution (SR) has become a popular solution in recent years, the ability of image SR is limited since much information is lost in input images. Inspired by the powerful information embedding ability of the encoder in image rescaling, in this paper, we introduce image rescaling to guide the training of image SR. Specifically, we add an adaption module before the SR network, and use the pre-trained rescaling network to g

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Lin, Huangxing, Yuhang Dong, Xinghao Ding, Tianpeng Liu, and Yongxiang Liu. "Unsupervised Pan-Sharpening via Mutually Guided Detail Restoration." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 4 (2024): 3386–94. http://dx.doi.org/10.1609/aaai.v38i4.28125.

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Pan-sharpening is a task that aims to super-resolve the low-resolution multispectral (LRMS) image with the guidance of a corresponding high-resolution panchromatic (PAN) image. The key challenge in pan-sharpening is to accurately modeling the relationship between the MS and PAN images. While supervised deep learning methods are commonly employed to address this task, the unavailability of ground-truth severely limits their effectiveness. In this paper, we propose a mutually guided detail restoration method for unsupervised pan-sharpening. Specifically, we treat pan-sharpening as a blind image

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TAHIR, Siti Zubaidah Mat, Hamimi OMAR, and Norhanim Abdul RAZAK. "NAVIGATING HERITAGE: THE DYNAMIC ROLES OF TOUR GUIDES IN KUALA LUMPUR’S HERITAGE WALKING TOURS." GeoJournal of Tourism and Geosites 58, no. 1 (2025): 306–14. https://doi.org/10.30892/gtg.58127-1412.

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Heritage walking tours have gained popularity as tourism offerings, signifying a growing demand for authentic and experiential experiences. The success of these tours depends not only on the historical importance of the sites visited, but also on the tour guides’ competence and skills in facilitating the experience. Despite their crucial role in the tourism industry, tour guides often lack recognition in many tourism plans and initiatives. This study explored tour guides’ perceptions of their roles in heritage walking tours in Kuala Lumpur, Malaysia. Data were collected from 11 certified tour

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Bouzos, Odysseas, Ioannis Andreadis, and Nikolaos Mitianoudis. "Conditional Random Field-Guided Multi-Focus Image Fusion." Journal of Imaging 8, no. 9 (2022): 240. http://dx.doi.org/10.3390/jimaging8090240.

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Multi-Focus image fusion is of great importance in order to cope with the limited Depth-of-Field of optical lenses. Since input images contain noise, multi-focus image fusion methods that support denoising are important. Transform-domain methods have been applied to image fusion, however, they are likely to produce artifacts. In order to cope with these issues, we introduce the Conditional Random Field (CRF) CRF-Guided fusion method. A novel Edge Aware Centering method is proposed and employed to extract the low and high frequencies of the input images. The Independent Component Analysis—ICA t

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Yang, Chen-Hsien, and Jih-Gau Juang. "Guide Robot Based on Image Processing and Path Planning." Machines 13, no. 7 (2025): 560. https://doi.org/10.3390/machines13070560.

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While guide dogs remain the primary aid for visually impaired individuals, robotic guides continue to be an important area of research. This study introduces an indoor guide robot designed to physically assist a blind person by holding their hand with a robotic arm and guiding them to a specified destination. To enable hand-holding, we employed a camera combined with object detection to identify the human hand and a closed-loop control system to manage the robotic arm’s movements. For path planning, we implemented a Dueling Double Deep Q Network (D3QN) enhanced with a genetic algorithm. To add

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Shirai, Keiichiro, Tatsuya Baba, Shunsuke Ono, Masahiro Okuda, Yusuke Tatesumi, and Paul Perrotin. "Guided Facial Skin Color Correction." Signals 2, no. 3 (2021): 540–58. http://dx.doi.org/10.3390/signals2030033.

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This paper proposes an automatic image correction method for portrait photographs, which promotes consistency of facial skin color by suppressing skin color changes due to background colors. In portrait photographs, skin color is often distorted due to the lighting environment (e.g., light reflected from a colored background wall and over-exposure by a camera strobe). This color distortion is emphasized when artificially synthesized with another background color, and the appearance becomes unnatural. In our framework, we, first, roughly extract the face region and rectify the skin color distri

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Sivakumar, V. "Review Made on the Content-Based Image Recovery." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (2022): 4911–17. http://dx.doi.org/10.22214/ijraset.2022.45973.

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Abstract: Images recovery mean that recovering the authentic images from which the images recovered from the feature database, as you will see inhere we talked in the paper all about the latest methods and technique in the field based on image recovery and image processing. Content Based Image Recovery (CBIR) is fastest and fastest developing research in field and in the place of the Graphic Processing. Translated methods facilitate faster image recovery, queries for image recovery system, image based on image processing (CBIR) in combination with multimedia encoded features, and outside many

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Qiang, Xiwen. "Remote Sensing of Atmospheric Turbulence Profiles by Laser Guide Stars." EPJ Web of Conferences 237 (2020): 06014. http://dx.doi.org/10.1051/epjconf/202023706014.

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Ranged-resolved profiles of atmospheric turbulence are necessary and important for many applications in astronomical and adaptive optics communities. In order to characterize the vertical atmospheric structure in field, a technique is put forward to remote sensing ranged-resolved profiles of atmospheric turbulence by combined with laser guide stars and differential image motion method. Laser guide stars are formed at several successive altitudes by projecting pulsed laser, returned signals of images are received by a optical system with two receiving telescopes, and variance of centroids′ dist

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Zhang, Xue, Xiushan Nie, Ziruo Sun, et al. "Re-ranking vehicle re-identification with orientation-guide query expansion." International Journal of Distributed Sensor Networks 18, no. 3 (2022): 155014772110663. http://dx.doi.org/10.1177/15501477211066305.

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Vehicle re-identification, which aims to retrieve information regarding a vehicle from different cameras with non-overlapping views, has recently attracted extensive attention in the field of computer vision owing to the development of smart cities. This task can be regarded as a type of retrieval problem, where re-ranking is important for performance enhancement. In the vehicle re-identification ranking list, images whose orientations are dissimilar to that of the query image must preferably be optimized on priority. However, traditional methods are incompatible with such samples, resulting i

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Zhan, Ying, Dan Hu, Xianchuan Yu, and Yufeng Wang. "Hyperspectral Image Classification Based on Mutually Guided Image Filtering." Remote Sensing 16, no. 5 (2024): 870. http://dx.doi.org/10.3390/rs16050870.

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Hyperspectral remote sensing images (HSIs) have both spectral and spatial characteristics. The adept exploitation of these attributes is central to enhancing the classification accuracy of HSIs. In order to effectively utilize spatial and spectral features to classify HSIs, this paper proposes a method for the spatial feature extraction of HSIs based on a mutually guided image filter (muGIF) and combined with the band-distance-grouped principal component. Firstly, aiming at the problem that previously guided image filtering cannot effectively deal with the inconsistent information structure be

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Rastogi, Alok Kumar, and A. K. Tiwari. "Metal wave-guide to dielectric image guide transition using exponential taper." International Journal of Infrared and Millimeter Waves 13, no. 12 (1992): 1895–914. http://dx.doi.org/10.1007/bf01011330.

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Tang, Hao, Philip Torr, and Nicu Sebe. "Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation." IEEE Transactions on Pattern Analysis and Machine Intelligence 45, no. 5 (2023): 6055–71. https://doi.org/10.1109/TPAMI.2022.3212915.

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We propose a novel model named Multi-Channel Attention Selection Generative Adversarial Network (SelectionGAN) for guided image-to-image translation, where we translate an input image into another while respecting an external semantic guidance. The proposed SelectionGAN explicitly utilizes the semantic guidance information and consists of two stages. In the first stage, the input image and the conditional semantic guidance are fed into a cycled semantic-guided generation network to produce initial coarse results. In the second stage, we refine the initial results by using the proposed multi-sc

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Sanjana, R., V. Sri Harshitha, K. Navyasree, G. Srija, M. Bharathi, and T. Aditya Sai Srinivas. "Glam Guidance: Empowering Your Fashion Choices with Image Insights." Journal of Image Processing and Image Restoration 2, no. 1 (2025): 1–5. https://doi.org/10.48001/joipir.2025.211-5.

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The paper introduces a Fashion Recommendation System that utilizes computer vision and machine learning to analyze fashion items' visual attributes such as color, texture, and style, offering similar or complementary product recommendations to users. It guides readers through the process of building such a system using Python. Leveraging a pre-trained Convolutional Neural Network (CNN), the system extracts feature from fashion images, enabling calculation of similarities between images for recommendation purposes. Employing cosine similarity, it provides personalized recommendations based on u

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Guo, Di, Xiaobo Qu, Xiaofeng Du, Keshou Wu, and Xuhui Chen. "Salt and Pepper Noise Removal with Noise Detection and a Patch-Based Sparse Representation." Advances in Multimedia 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/682747.

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Images may be corrupted by salt and pepper impulse noise due to noisy sensors or channel transmission errors. A denoising method by detecting noise candidates and enforcing image sparsity with a patch-based sparse representation is proposed. First, noise candidates are detected and an initial guide image is obtained via an adaptive median filtering; second, a patch-based sparse representation is learnt from this guide image; third, a weightedl1-l1regularization method is proposed to penalize the noise candidates heavier than the rest of pixels. An alternating direction minimization algorithm i

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