摘要 :
Instance retrieval is a fundamental problem in the multimedia field for its various applications. Since the relevancy is defined at the instance level, it is more challenging comparing to traditional image retrieval methods. Recen...
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Instance retrieval is a fundamental problem in the multimedia field for its various applications. Since the relevancy is defined at the instance level, it is more challenging comparing to traditional image retrieval methods. Recent advances show that Convolutional Neural Networks (CNNs) offer an attractive method for image feature representations. However, the CNN method extracts features from the whole image, thus the extracted features contain a large amount of background noisy information, leading to poor retrieval performance. To solve the problem, this paper proposed a deep region CNN method with object detection for instance-level object retrieval, which has two phases, i.e., offline Faster R-CNN training and online instance retrieval. First, we train a Faster R-CNN model to better locate the region of the objects. Second, we extract the CNN features from the detected object image region and then retrieve relevant images based on the visual similarity of these features. Furthermore, we utilized three different strategies for feature fusing based on the detected object region candidates from Faster R-CNN. We conduct the experiment on a large dataset: INSTRE with 23,070 object images and additional one million distractor images. Qualitative and quantitative evaluation results have demonstrated the advantage of our proposed method. In addition, we conducted extensive experiments on the Oxford dataset and the experimental results further validated the effectiveness of our proposed method.
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Over the last several decades, researches on visual object retrieval and recognition have achieved fast and remarkable success. However, while the category-level tasks prevail in the community, the instance-level tasks (especially...
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Over the last several decades, researches on visual object retrieval and recognition have achieved fast and remarkable success. However, while the category-level tasks prevail in the community, the instance-level tasks (especially recognition) have not yet received adequate focuses. Applications such as content-based search engine and robot vision systems have alerted the awareness to bring instance-level tasks into a more realistic and challenging scenario. Motivated by the limited scope of existing instance-level datasets, in this article we propose a new benchmark for INSTance-level visual object REtrieval and REcognition (INSTRE). Compared with existing datasets, INSTRE has the following major properties: (1) balanced data scale, (2) more diverse intraclass instance variations, (3) cluttered and less contextual backgrounds, (4) object localization annotation for each image, (5) well-manipulated double-labelled images for measuring multiple object (within one image) case. We will quantify and visualize the merits of INSTRE data, and extensively compare them against existing datasets. Then on INSTRE, we comprehensively evaluate several popular algorithms to large-scale object retrieval problem with multiple evaluation metrics. Experimental results show that all the methods suffer a performance drop on INSTRE, proving that this field still remains a challenging problem. Finally we integrate these algorithms into a simple yet efficient scheme for recognition and compare it with classification-based methods. Importantly, we introduce the realistic multiobjects recognition problem. All experiments are conducted in both single object case and multiple objects case.
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Research Journal of Topical and Cosmetic Sciences(RJTCS)[ISSN 2321-5844(Online)0976-2981(Print)] is an international,peer-reviewed journal,correspondence in the fields of skin and cosmetic research.The aim of RJTCS is to publishes...
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Research Journal of Topical and Cosmetic Sciences(RJTCS)[ISSN 2321-5844(Online)0976-2981(Print)] is an international,peer-reviewed journal,correspondence in the fields of skin and cosmetic research.The aim of RJTCS is to publishes Original research Articles,Short Communications,Review Articles in both pure and applied areas in cosmetic sciences.The area includes cosmetics,toiletries,perfumery and the formulations used on testing of skin,hair and oral products,physical chemistry and technology used in cosmetic emulsion and dispersed systems,theory and application of surfactants,olfactive research,aerosol technology and selected aspects of standardization of cosmetic formulations and its analytical chemistry.The journal is published Semi-annually every year in last week of June and December.
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Please note that the name of the last author in the above author list is wrongly spelled. The author name should read: A. Braem. We apologize for any inconvenience caused.
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Objetivo levantar a prevalência dos fatores intrínsecos e extrínsecos que podem interferir no processo de aprendizagem em crianças com epilepsia. Métodos este estudo descritivo foi realizado no Ambulatório de Neurologia Infantil d...
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Objetivo levantar a prevalência dos fatores intrínsecos e extrínsecos que podem interferir no processo de aprendizagem em crianças com epilepsia. Métodos este estudo descritivo foi realizado no Ambulatório de Neurologia Infantil do Hospital de Pediatria Professor Heriberto Bezerra (HOSPED) da UFRN. A obtenção dos dados ocorreu durante setembro/2009 a março/2010 por meio da aplicação de um questionário com pais e cuidadores de crianças com epilepsia. A amostra foi constituída por 41 crianças, seguindo os seguintes critérios de inclusão: a) pais ou cuidadores de crianças com diagnóstico inequívoco de epilepsia atendidas no ambulatório do HOSPED; b) crianças com idades entre 3 e 12 anos; e c) pais ou responsáveis assinarem o termo de consentimento livre e esclarecido. Resultados 61% das crianças apresentaram diagnóstico de epilepsia pura. 59% tiveram sua primeira crise antes dos 03 anos de idade. 34% apresentavam crises do tipo generalizada. 51% apresentavam crises no período da pesquisa. 98% estavam em tratamento medicamentoso para controle das crises, sendo 55% monoterapia e 45% politerapia. 76% estavam inseridas na escola, sendo 50% em escolas públicas. 66% nunca repetiram o ano. 49% das crianças tiveram assiduidade escolar prejudicada em virtude das crises. 64% nunca foram excluídas da escola pelos professores devido a epilepsia e 85% dos pais afirmaram superproteger os filhos. Conclusão o estudo concluiu que, além da epilepsia, as crianças com essa patologia são também expostas a outros fatores, decorrentes da doença, que podem influenciar negativamente no processo de aprendizagem dessas crianças.
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An author's name was listed incorrectly as "Kouichi Awazu" in the December 2007 article "Birefringence in optical fibers formed by proton implantation" [Nucl. Instr, and Meth. B 265 (2007) 490]. The author's name should be revised...
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An author's name was listed incorrectly as "Kouichi Awazu" in the December 2007 article "Birefringence in optical fibers formed by proton implantation" [Nucl. Instr, and Meth. B 265 (2007) 490]. The author's name should be revised to "Koichi Awazu". This correction has no effect on the conclusion of the article.
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