Relevant bibliographies by topics / Local visual feature

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Local visual feature'

Author: Grafiati
Published: 10 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Local visual feature"

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Jia, Xi Bin, and Mei Xia Zheng. "Video Based Visual Speech Feature Model Construction." Applied Mechanics and Materials 182-183 (June 2012): 1367–71. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.1367.

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This paper aims to give a solutions for the construction of chinese visual speech feature model based on HMM. We propose and discuss three kind representation model of the visual speech which are lip geometrical features, lip motion features and lip texture features. The model combines the advantages of the local LBP and global DCT texture information together, which shows better performance than the single feature. Equally the model combines the advantages of the local LBP and geometrical information together is better than single feature. By computing the recognition rate of the visemes from
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Wang, Yin-Tien, Chen-Tung Chi, and Ying-Chieh Feng. "Robot mapping using local invariant feature detectors." Engineering Computations 31, no. 2 (2014): 297–316. http://dx.doi.org/10.1108/ec-01-2013-0024.

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Purpose – To build a persistent map with visual landmarks is one of the most important steps for implementing the visual simultaneous localization and mapping (SLAM). The corner detector is a common method utilized to detect visual landmarks for constructing a map of the environment. However, due to the scale-variant characteristic of corner detection, extensive computational cost is needed to recover the scale and orientation of corner features in SLAM tasks. The purpose of this paper is to build the map using a local invariant feature detector, namely speeded-up robust features (SURF), to de
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Huang, Cuiyang, and Zihan Hu. "A multimodal transformer-based visual question answering method integrating local and global information." PLOS One 20, no. 7 (2025): e0324757. https://doi.org/10.1371/journal.pone.0324757.

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Addressing the limitations in current visual question answering (VQA) models face limitations in multimodal feature fusion capabilities and often lack adequate consideration of local information, this study proposes a multimodal Transformer VQA network based on local and global information integration (LGMTNet). LGMTNet employs attention on local features within the context of global features, enabling it to capture both broad and detailed image information simultaneously, constructing a deep encoder-decoder module that directs image feature attention based on the question context, thereby enh
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Zhang, Yuanpeng, Jingye Guan, Haobo Wang, Kaiming Li, Ying Luo, and Qun Zhang. "Generalized Zero-Shot Space Target Recognition Based on Global-Local Visual Feature Embedding Network." Remote Sensing 15, no. 21 (2023): 5156. http://dx.doi.org/10.3390/rs15215156.

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Existing deep learning-based space target recognition methods rely on abundantly labeled samples and are not capable of recognizing samples from unseen classes without training. In this article, based on generalized zero-shot learning (GZSL), we propose a space target recognition framework to simultaneously recognize space targets from both seen and unseen classes. First, we defined semantic attributes to describe the characteristics of different categories of space targets. Second, we constructed a dual-branch neural network, termed the global-local visual feature embedding network (GLVFENet)
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Sun, Huadong, Xu Zhang, Xiaowei Han, Xuesong Jin, and Zhijie Zhao. "Commodity Image Classification Based on Improved Bag-of-Visual-Words Model." Complexity 2021 (March 17, 2021): 1–10. http://dx.doi.org/10.1155/2021/5556899.

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With the increasing scale of e-commerce, the complexity of image content makes commodity image classification face great challenges. Image feature extraction often determines the quality of the final classification results. At present, the image feature extraction part mainly includes the underlying visual feature and the intermediate semantic feature. The intermediate semantics of the image acts as a bridge between the underlying features and the advanced semantics of the image, which can make up for the semantic gap to a certain extent and has strong robustness. As a typical intermediate sem
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Dong, Baoyu, and Guang Ren. "A New Scene Classification Method Based on Local Gabor Features." Mathematical Problems in Engineering 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/109718.

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A new scene classification method is proposed based on the combination of local Gabor features with a spatial pyramid matching model. First, new local Gabor feature descriptors are extracted from dense sampling patches of scene images. These local feature descriptors are embedded into a bag-of-visual-words (BOVW) model, which is combined with a spatial pyramid matching framework. The new local Gabor feature descriptors have sufficient discrimination abilities for dense regions of scene images. Then the efficient feature vectors of scene images can be obtained byK-means clustering method and vi
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N. Sultani, Zainab, and Ban N. Dhannoon. "Modified Bag of Visual Words Model for Image Classification." Al-Nahrain Journal of Science 24, no. 2 (2021): 78–86. http://dx.doi.org/10.22401/anjs.24.2.11.

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Image classification is acknowledged as one of the most critical and challenging tasks in computer vision. The bag of visual words (BoVW) model has proven to be very efficient for image classification tasks since it can effectively represent distinctive image features in vector space. In this paper, BoVW using Scale-Invariant Feature Transform (SIFT) and Oriented Fast and Rotated BRIEF(ORB) descriptors are adapted for image classification. We propose a novel image classification system using image local feature information obtained from both SIFT and ORB local feature descriptors. As a result,
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Gao, Yuhang, and Long Zhao. "Coarse TRVO: A Robust Visual Odometry with Detector-Free Local Feature." Journal of Advanced Computational Intelligence and Intelligent Informatics 26, no. 5 (2022): 731–39. http://dx.doi.org/10.20965/jaciii.2022.p0731.

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The visual SLAM system requires precise localization. To obtain consistent feature matching results, visual features acquired by neural networks are being increasingly used to replace traditional manual features in situations with weak texture, motion blur, or repeated patterns. However, to improve the level of accuracy, most deep learning enhanced SLAM systems, which have a decreased efficiency. In this paper, we propose Coarse TRVO, a visual odometry system that uses deep learning for feature matching. The deep learning network uses a CNN and transformer structures to provide dense high-qual
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Aw, Y. K., Robyn Owens, and John Ross. "An analysis of local energy and phase congruency models in visual feature detection." Journal of the Australian Mathematical Society. Series B. Applied Mathematics 40, no. 1 (1998): 97–122. http://dx.doi.org/10.1017/s0334270000012406.

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AbstractA variety of approaches have been developed for the detection of features such as edges, lines, and corners in images. Many techniques presuppose the feature type, such as a step edge, and use the differential properties of the luminance function to detect the location of such features. The local energy model provides an alternative approach, detecting a variety of feature types in a single pass by analysing order in the phase components of the Fourier transform of the image. The local energy model is usually implemented by calculating the envelope of the analytic signal associated wit
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Manandhar, Dipu, Kim-Hui Yap, Zhenwei Miao, and Lap-Pui Chau. "Lattice-Support repetitive local feature detection for visual search." Pattern Recognition Letters 98 (October 2017): 123–29. http://dx.doi.org/10.1016/j.patrec.2017.09.021.

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Dissertations / Theses on the topic "Local visual feature"

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Andreasson, Henrik. "Local visual feature based localisation and mapping by mobile robots." Doctoral thesis, Örebro : Örebro University, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-2444.

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Manivannan, Siyamalan. "Visual feature learning with application to medical image classification." Thesis, University of Dundee, 2015. https://discovery.dundee.ac.uk/en/studentTheses/10e26212-e836-4ccd-9b12-a576458de5eb.

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Various hand-crafted features have been explored for medical image classification, which include SIFT and Local Binary Patterns (LBP). However, hand-crafted features may not be optimally discriminative for classifying images from particular domains (e.g. colonoscopy), as not necessarily tuned to the domain’s characteristics. In this work, I give emphasis on learning highly discriminative local features and image representations to achieve the best possible classification performance for medical images, particularly for colonoscopy and histology (cell) images. I propose approaches to learn loca
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Emir, Erdem. "A Comparative Performance Evaluation Of Scale Invariant Interest Point Detectors For Infrared And Visual Images." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12610159/index.pdf.

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In this thesis, the performance of four state-of-the-art feature detectors along with SIFT and SURF descriptors in matching object features of mid-wave infrared, long-wave infrared and visual-band images is evaluated across viewpoints and changing distance conditions. The utilized feature detectors are Scale Invariant Feature Transform (SIFT), multiscale Harris-Laplace, multiscale Hessian-Laplace and Speeded Up Robust Features (SURF) detectors, all of which are invariant to image scale and rotation. Features on different blackbodies, human face and vehicle images are extracted and performance
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Ferro, Demetrio. "Effects of attention on visual processing between cortical layers and cortical areas V1 and V4." Doctoral thesis, Università degli studi di Trento, 2019. http://hdl.handle.net/11572/246290.

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Visual attention improves sensory processing, as well as perceptual readout and behavior. Over the last decades, many proposals have been put forth to explain how attention affects visual neural processing. These include the modulation of neural firing rates and synchrony, neural tuning properties, and rhythmic, subthreshold activity. Despite the wealth of knowledge provided by previous studies, the way attention shapes interactions between cortical layers within and between visual sensory areas is only just emerging. To investigate this, we studied neural signals from macaque V1 and V4 visual
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Ferro, Demetrio. "Effects of attention on visual processing between cortical layers and cortical areas V1 and V4." Doctoral thesis, Università degli studi di Trento, 2019. http://hdl.handle.net/11572/246290.

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Visual attention improves sensory processing, as well as perceptual readout and behavior. Over the last decades, many proposals have been put forth to explain how attention affects visual neural processing. These include the modulation of neural firing rates and synchrony, neural tuning properties, and rhythmic, subthreshold activity. Despite the wealth of knowledge provided by previous studies, the way attention shapes interactions between cortical layers within and between visual sensory areas is only just emerging. To investigate this, we studied neural signals from macaque V1 and V4 visual
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Zhu, Chao. "Effective and efficient visual description based on local binary patterns and gradient distribution for object recognition." Phd thesis, Ecole Centrale de Lyon, 2012. http://tel.archives-ouvertes.fr/tel-00755644.

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Cette thèse est consacrée au problème de la reconnaissance visuelle des objets basé sur l'ordinateur, qui est devenue un sujet de recherche très populaire et important ces dernières années grâce à ses nombreuses applications comme l'indexation et la recherche d'image et de vidéo , le contrôle d'accès de sécurité, la surveillance vidéo, etc. Malgré beaucoup d'efforts et de progrès qui ont été fait pendant les dernières années, il reste un problème ouvert et est encore considéré comme l'un des problèmes les plus difficiles dans la communauté de vision par ordinateur, principalement en raison des
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Abid, Muhammad Rizwan. "Visual Recognition of a Dynamic Arm Gesture Language for Human-Robot and Inter-Robot Communication." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32800.

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This thesis presents a novel Dynamic Gesture Language Recognition (DGLR) system for human-robot and inter-robot communication. We developed and implemented an experimental setup consisting of a humanoid robot/android able to recognize and execute in real time all the arm gestures of the Dynamic Gesture Language (DGL) in similar way as humans do. Our DGLR system comprises two main subsystems: an image processing (IP) module and a linguistic recognition system (LRS) module. The IP module enables recognizing individual DGL gestures. In this module, we use the bag-of-features (BOFs) and a local
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Ventura, Royo Carles. "Visual object analysis using regions and local features." Doctoral thesis, Universitat Politècnica de Catalunya, 2016. http://hdl.handle.net/10803/398407.

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The first part of this dissertation focuses on an analysis of the spatial context in semantic image segmentation. First, we review how spatial context has been tackled in the literature by local features and spatial aggregation techniques. From a discussion about whether the context is beneficial or not for object recognition, we extend a Figure-Border-Ground segmentation for local feature aggregation with ground truth annotations to a more realistic scenario where object proposals techniques are used instead. Whereas the Figure and Ground regions represent the object and the surround respecti
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Bai, Hequn. "Mobile 3D Visual Search based on Local Stereo Image Features." Thesis, KTH, Ljud- och bildbehandling, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-102603.

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Many recent applications using local image features focus on 2D image recognition. Such applications can not distinguish between real objects and photos of objects. In this project, we present a 3D object recognition method using stereo images. Using the 3D information of the objects obtained from stereo images, objects with similar image description but different 3D shapes can be distinguished, such as real objects and photos of objects. Besides, the feature matching performance is improved compared with the method using only local image features. Knowing the fact that local image features ma
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Le, Viet Phuong. "Logo detection, recognition and spotting in context by matching local visual features." Thesis, La Rochelle, 2015. http://www.theses.fr/2015LAROS029/document.

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Cette thèse présente un framework pour le logo spotting appliqué à repérer les logos à partir de l’image des documents en se concentrant sur la catégorisation de documents et les problèmes de récupération de documents. Nous présentons également trois méthodes de matching par point clé : le point clé simple avec le plus proche voisin, le matching par règle des deux voisins les plus proches et le matching par deux descripteurs locaux à différents étapes de matching. Les deux derniers procédés sont des améliorations de la première méthode. En outre, utiliser la méthode de classification basée sur
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Books on the topic "Local visual feature"

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O’Neal, M. Angela. Postpartum Visual Disturbance. Edited by Angela O’Neal. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190609917.003.0017.

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Preeclampsia (PE) is a multi-organ system disorder defined as hypertension with blood pressures greater than 140/90 on two occasions and proteinuria of more than 300 mg/24 hours. Eclampsia is defined as when seizures occur in a woman with preeclampsia. The pathophysiology of preeclampsia/eclampsia is felt to be related to incomplete penetration of the cytotrophoblasts of the placenta into the myometrium, leading to local ischemia, propagation of ischemic factors causing hypertension, resulting in endothelial dysfunction. The clinical features are related to which end organ is involved: in the
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Wade, Nicholas J. Hidden Images. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199794607.003.0113.

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It is relatively easy to hide pictorial images, but this is of little value if they remain hidden. Presenting hidden images for visual purposes is a modern preoccupation, and some of the perceptual processes involved in them are described in this chapter. Pictorial images can be concealed in terms of detection or recognition. In both cases there is interplay between the global features of the concealed image and the local elements that carry it. Gestalt grouping principles can hinder as well as help recognition. Examples of images (mostly faces) hidden in geometrical designs and text as well a
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Forshaw, Joseph, and William Cooper. Pigeons and Doves in Australia. CSIRO Publishing, 2015. http://dx.doi.org/10.1071/9781486304042.

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Possibly the most successful urban birds, pigeons and doves in the Order Columbiformes are one of the most easily recognised groups. They are an ancient and very successful group with an almost worldwide distribution and are most strongly represented in tropical and subtropical regions, including Australia. In most species simple plumage patterns feature mainly grey and brown with black, white or dull reddish markings, but the highly colourful fruit-doves include some of the most beautiful of all birds.
 From dense rainforests of north Queensland, where brilliantly plumaged Superb Fruit-D
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Ilan, Jonathan, and Gregory J. Snyder. Graffiti. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199935383.013.144.

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Graffiti writing is often intensely policed despite being a relatively low-harm crime. Graffiti can be read by members of the public as a visual indicator of lawlessness and thus induce a certain amount of alarm. While there are a range of different kinds of graffiti, the most ubiquitous is that practiced by subcultural “writers.” Research indicates that there is an order and logic to writing. Writers often cultivate skills, experiences, and dispositions that imbue them with particular value in the postindustrial economy, offering them heightened career prospects. Graffiti and street art are i
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Eitan, Zohar, Renee Timmers, and Mordechai Adler. Cross-modal correspondences and affect in a Schubert song. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199351411.003.0006.

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Light, distance and motion are prominent features in Heine’s ‘Am fernen Horizonten’. A city is veiled in dusk, the sun rises from the earth and the boatman rows with sad strokes. Using empirical findings on cross-modal and affective associations with sounds, we examine Schubert’s interpretation and illustration of these metaphorical dimensions in ‘Die Stadt’. Focusing on local variations in tempo and dynamics, we analyse how the emotional and cross-modal connotations of the song are modified in three performances, provindinginsight into the interrelationship between cross-modal and affective c
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Stamenkoviç, Marko, ed. Resistance. 2nd ed. punctum books, 2021. http://dx.doi.org/10.53288/0384.1.00.

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esistance features a selection of overtly non-conformist positions in the contemporary visual art scene of Albania vis-à-vis the most recent social, political, and economic turmoils in the Western Balkans – a region marked by the dark side of political governances that have remained “democratic” in their outward appearance (especially toward the European Union), while dramatically leaning toward autocratic regimes in the eyes of their own citizens. Regardless of their citizens’ primary interests, and despite some positive signals surfacing in the international media, almost every attempt to es
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Book chapters on the topic "Local visual feature"

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Gruchalla, Kenny, Mark Rast, Elizabeth Bradley, and Pablo Mininni. "Segmentation and Visualization of Multivariate Features Using Feature-Local Distributions." In Advances in Visual Computing. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24028-7_57.

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Razali, Mohd Norhisham, Noridayu Manshor, Alfian Abdul Halin, Razali Yaakob, and Norwati Mustapha. "Food Category Recognition Using SURF and MSER Local Feature Representation." In Advances in Visual Informatics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70010-6_20.

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Shi, Xun, Neil D. B. Bruce, and John K. Tsotsos. "Biologically Motivated Local Contextual Modulation Improves Low-Level Visual Feature Representations." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31295-3_10.

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Turcsany, Diana, and Andrzej Bargiela. "Learning Local Receptive Fields in Deep Belief Networks for Visual Feature Detection." In Neural Information Processing. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12637-1_58.

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Xu, Xin, and Jie Wang. "Extended Non-local Feature for Visual Saliency Detection in Low Contrast Images." In Lecture Notes in Computer Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11018-5_46.

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Lu, Huimin, Hui Zhang, and Zhiqiang Zheng. "A Novel Real-Time Local Visual Feature for Omnidirectional Vision Based on FAST and LBP." In RoboCup 2010: Robot Soccer World Cup XIV. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20217-9_25.

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Liu, Jiuming, Dong Zhuo, Zhiheng Feng, et al. "DVLO: Deep Visual-LiDAR Odometry with Local-to-Global Feature Fusion and Bi-directional Structure Alignment." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-72684-2_27.

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Lin, Wanyan, Hao Yi, and Xiumin Li. "Image Reconstruction and Recognition of Optical Flow Based on Local Feature Extraction Mechanism of Visual Cortex." In International Conference on Neural Computing for Advanced Applications. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-5844-3_2.

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Khellat-Kihel, Souad, Zhenan Sun, and Massimo Tistarelli. "An Hybrid Attention-Based System for the Prediction of Facial Attributes." In Lecture Notes in Computer Science. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82427-3_9.

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AbstractRecent research on face analysis has demonstrated the richness of information embedded in feature vectors extracted from a deep convolutional neural network. Even though deep learning achieved a very high performance on several challenging visual tasks, such as determining the identity, age, gender and race, it still lacks a well grounded theory which allows to properly understand the processes taking place inside the network layers. Therefore, most of the underlying processes are unknown and not easy to control. On the other hand, the human visual system follows a well understood proc
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Huang, Jiqian, Shuo Yu, Hehan Zhou, Guoguang Wang, and Hao Zheng. "Exploring Optimized Generation Methods for Post-War Cityscapes Restoration Based on Stable Diffusion Model." In Computational Design and Robotic Fabrication. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-3433-0_23.

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Abstract Nowadays, frequent local wars have inflicted severe damage on urban built environments, presenting substantial challenges for post-war restoration. Moreover, the scarcity of architectural imagery further exacerbates these challenges. In this context, virtual restoration techniques have shown significant advantages in speed and accuracy over traditional experience-based methods. This paper aims to explore the potential of artificial intelligence in the restoration of architectural ruins and the generation of visual predictions. Specifically, we compared the performance of pix2pix GAN a
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Conference papers on the topic "Local visual feature"

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dos Santos, Wagner Luiz Oliveira, and Anselmo Antunes Montenegro. "Breaking Visual Similarity Barriers: Enhanced Image Identification Through Global-Local Feature Fusion." In 2024 37th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI). IEEE, 2024. http://dx.doi.org/10.1109/sibgrapi62404.2024.10716315.

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He, Yi, Lei Yang, and Shilin Wang. "Enhancing Visual Forced Alignment with Local Context-Aware Feature Extraction and Multi-Task Learning." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10889781.

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Song, Wenzheng, Ran Yan, Boshu Lei, and Takayuki Okatani. "Globalizing Local Features: Image Retrieval Using Shared Local Features with Pose Estimation for Faster Visual Localization." In 2024 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2024. http://dx.doi.org/10.1109/icra57147.2024.10610786.

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Ikeda, Iori, Miho Adachi, and Ryusuke Miyamoto. "Score Calculation with Local and Global Features for Visual Place Recognition." In TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON). IEEE, 2024. https://doi.org/10.1109/tencon61640.2024.10902810.

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Han, Yuping, Yajing Xu, Shishuo Liu, Sheng Gao, and Si Li. "Visual Relationship Detection Based on Local Feature and Context Feature." In 2018 International Conference on Network Infrastructure and Digital Content (IC-NIDC). IEEE, 2018. http://dx.doi.org/10.1109/icnidc.2018.8525683.

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Xu, Jingtao, Qiaohong Li, Peng Ye, Haiqing Du, and Yong Liu. "Local feature aggregation for blind image quality assessment." In 2015 Visual Communications and Image Processing (VCIP). IEEE, 2015. http://dx.doi.org/10.1109/vcip.2015.7457832.

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El-Gaaly, Tarek, Marwan Torki, and Ahmed Elgammal. "Spatial-Visual Label Propagation for Local Feature Classification." In 2014 22nd International Conference on Pattern Recognition (ICPR). IEEE, 2014. http://dx.doi.org/10.1109/icpr.2014.589.

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Zhou, Wengang, Houqiang Li, and Qi Tian. "Scalable local feature matching without visual codebook training." In the 7th International Conference. ACM Press, 2015. http://dx.doi.org/10.1145/2808492.2808575.

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Anh, La Tuan, and Jae-Bok Song. "Object tracking and visual servoing using features computed from local feature descriptor." In 2010 International Conference on Control, Automation and Systems (ICCAS 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccas.2010.5669666.

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Bucak, Serhat, Ankur Saxena, Abhishek Nagar, Felix Fernandes, and Kong-Posh Bhat. "Mid-level feature based local descriptor selection for image search." In 2013 Visual Communications and Image Processing (VCIP). IEEE, 2013. http://dx.doi.org/10.1109/vcip.2013.6706455.

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Reports on the topic "Local visual feature"

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Maguire, Sasha. Amplifying Voices. Celebrating Design. Women Who Design. Montana State University, 2025. https://doi.org/10.15788/1751923449.

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Women Who Design is a research project dedicated to amplifying the stories, challenges, and achievements of women designers in Bozeman. Through interviews, visual storytelling, and curated work samples, this project highlights their creative processes and showcases the unique contributions of local designers, shedding light on their impact within both the industry and the broader community.By documenting and sharing these stories, Women Who Design seeks to foster greater recognition and appreciation for women in the design field while creating a lasting resource for aspiring designers. This pr
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