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AYANKOSO, Micheal Taiwo, Damilola Miracle OLUWAGBAMILA et Olugbenga Samson ABE. « EFFECTS OF ACTIVATED CHARCOAL ON LIVESTOCK PRODUCTION : A REVIEW ». Slovak Journal of Animal Science 56, no 01 (31 mars 2023) : 46–60. http://dx.doi.org/10.36547/sjas.791.

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Thinh, Nguyen Hong, Tran Hoang Tung et Le Vu Ha. « Depth-aware salient object segmentation ». VNU Journal of Science : Computer Science and Communication Engineering 36, no 2 (7 octobre 2020). http://dx.doi.org/10.25073/2588-1086/vnucsce.217.

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Object segmentation is an important task which is widely employed in many computer vision applications such as object detection, tracking, recognition, and retrieval. It can be seen as a two-phase process: object detection and segmentation. Object segmentation becomes more challenging in case there is no prior knowledge about the object in the scene. In such conditions, visual attention analysis via saliency mapping may offer a mean to predict the object location by using visual contrast, local or global, to identify regions that draw strong attention in the image. However, in such situations as clutter background, highly varied object surface, or shadow, regular and salient object segmentation approaches based on a single image feature such as color or brightness have shown to be insufficient for the task. This work proposes a new salient object segmentation method which uses a depth map obtained from the input image for enhancing the accuracy of saliency mapping. A deep learning-based method is employed for depth map estimation. Our experiments showed that the proposed method outperforms other state-of-the-art object segmentation algorithms in terms of recall and precision. KeywordsSaliency map, Depth map, deep learning, object segmentation References[1] Itti, C. Koch, E. Niebur, A model of saliency-based visual attention for rapid scene analysis, IEEE Transactions on pattern analysis and machine intelligence 20(11) (1998) 1254-1259.[2] Goferman, L. Zelnik-Manor, A. Tal, Context-aware saliency detection, IEEE transactions on pattern analysis and machine intelligence 34(10) (2012) 1915-1926.[3] Kanan, M.H. Tong, L. Zhang, G.W. Cottrell, Sun: Top-down saliency using natural statistics, Visual cognition 17(6-7) (2009) 979-1003.[4] Liu, Z. Yuan, J. Sun, J. Wang, N. Zheng, X. Tang, H.-Y. Shum, Learning to detect a salient object, IEEE Transactions on Pattern analysis and machine intelligence 33(2) (2011) 353-367.[5] Perazzi, P. Krähenbühl, Y. Pritch, A. Hornung, Saliency filters: Contrast based filtering for salient region detection, in: Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, IEEE, 2012, pp. 733-740.[6] M. Cheng, N.J. Mitra, X. Huang, P.H. Torr, S.M. Hu, Global contrast based salient region detection, IEEE Transactions on Pattern Analysis and Machine Intelligence 37(3) (2015) 569-582.[7] Borji, L. Itti, State-of-the-art in visual attention modeling, IEEE transactions on pattern analysis and machine intelligence 35(1) (2013) 185-207.[8] Simonyan, A. Vedaldi, A. Zisserman, Deep inside convolutional networks: Visualising image classification models and saliency maps, arXiv preprint arXiv:1312.6034.[9] Li, Y. Yu, Visual saliency based on multiscale deep features, in: Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 5455-5463.[10] Liu, J. Han, Dhsnet: Deep hierarchical saliency network for salient object detection, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 678-686.[11] Achanta, S. Hemami, F. Estrada, S. Susstrunk, Frequency-tuned saliency detection model, CVPR: Proc IEEE, 2009, pp. 1597-604.Fu, J. Cheng, Z. Li, H. Lu, Saliency cuts: An automatic approach to object segmentation, in: Pattern Recognition, 2008. ICPR 2008. 19th International Conference on, IEEE, 2008, pp. 1-4Borenstein, J. Malik, Shape guided object segmentation, in: Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, Vol. 1, IEEE, 2006, pp. 969-976.Jiang, J. Wang, Z. Yuan, T. Liu, N. Zheng, S. Li, Automatic salient object segmentation based on context and shape prior., in: BMVC. 6 (2011) 9.Ciptadi, T. Hermans, J.M. Rehg, An in depth view of saliency, Georgia Institute of Technology, 2013.Desingh, K.M. Krishna, D. Rajan, C. Jawahar, Depth really matters: Improving visual salient region detection with depth., in: BMVC, 2013.Li, J. Ye, Y. Ji, H. Ling, J. Yu, Saliency detection on light field, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2014, pp. 2806-2813.Koch, S. Ullman, Shifts in selective visual attention: towards the underlying neural circuitry, in: Matters of intelligence, Springer, 1987, pp. 115-141.Laina, C. Rupprecht, V. Belagiannis, F. Tombari, N. Navab, Deeper depth prediction with fully convolutional residual networks, in: 3D Vision (3DV), 2016 Fourth International Conference on, IEEE, 2016, pp. 239-248.Bruce, J. Tsotsos, Saliency based on information maximization, in: Advances in neural information processing systems, 2006, pp. 155-162.Ren, X. Gong, L. Yu, W. Zhou, M. Ying Yang, Exploiting global priors for rgb-d saliency detection, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2015, pp. 25-32.Fang, J. Wang, M. Narwaria, P. Le Callet, W. Lin, Saliency detection for stereoscopic images., IEEE Trans. Image Processing 23(6) (2014) 2625-2636.Hou, L. Zhang, Saliency detection: A spectral residual approach, in: Computer Vision and Pattern Recognition, 2007. CVPR’07. IEEE Conference on, IEEE, 2007, pp. 1-8.Guo, Q. Ma, L. Zhang, Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform, in: Computer vision and pattern recognition, 2008. cvpr 2008. ieee conference on, IEEE, 2008, pp. 1-8.Fang, W. Lin, B.S. Lee, C.T. Lau, Z. Chen, C.W. Lin, Bottom-up saliency detection model based on human visual sensitivity and amplitude spectrum, IEEE Transactions on Multimedia 14(1) (2012) 187-198.Lang, T.V. Nguyen, H. Katti, K. Yadati, M. Kankanhalli, S. Yan, Depth matters: Influence of depth cues on visual saliency, in: Computer vision-ECCV 2012, Springer, 2012, pp. 101-115.Zhang, G. Jiang, M. Yu, K. Chen, Stereoscopic visual attention model for 3d video, in: International Conference on Multimedia Modeling, Springer, 2010, pp. 314-324.Wang, M.P. Da Silva, P. Le Callet, V. Ricordel, Computational model of stereoscopic 3d visual saliency, IEEE Transactions on Image Processing 22(6) (2013) 2151-2165.Peng, B. Li, W. Xiong, W. Hu, R. Ji, Rgbd salient object detection: A benchmark and algorithms, in: European Conference on Computer Vision (ECCV), 2014, pp. 92-109.Wu, L. Duan, L. Kong, Rgb-d salient object detection via feature fusion and multi-scale enhancement, in: CCF Chinese Conference on Computer Vision, Springer, 2015, pp. 359-368.Xue, Y. Gu, Y. Li, J. Yang, Rgb-d saliency detection via mutual guided manifold ranking, in: Image Processing (ICIP), 2015 IEEE International Conference on, IEEE, 2015, pp. 666-670.Katz, A. Adler, Depth camera based on structured light and stereo vision, uS Patent App. 12/877,595 (Mar. 8 2012).Chatterjee, G. Molina, D. Lelescu, Systems and methods for determining depth from multiple views of a scene that include aliasing using hypothesized fusion, uS Patent App. 13/623,091 (Mar. 21 2013).Matthies, T. Kanade, R. Szeliski, Kalman filter-based algorithms for estimating depth from image sequences, International Journal of Computer Vision 3(3) (1989) 209-238.Y. Schechner, N. Kiryati, Depth from defocus vs. stereo: How different really are they?, International Journal of Computer Vision 39(2) (2000) 141-162.Delage, H. Lee, A.Y. Ng, A dynamic bayesian network model for autonomous 3d reconstruction from a single indoor image, in: Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, Vol. 2, IEEE, 2006, pp. 2418-2428.Saxena, M. Sun, A.Y. Ng, Make3d: Learning 3d scene structure from a single still image, IEEE transactions on pattern analysis and machine intelligence 31(5) (2009) 824-840.Hedau, D. Hoiem, D. Forsyth, Recovering the spatial layout of cluttered rooms, in: Computer vision, 2009 IEEE 12th international conference on, IEEE, 2009, pp. 1849-1856.Liu, S. Gould, D. Koller, Single image depth estimation from predicted semantic labels, in: Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on, IEEE, 2010, pp. 1253-1260.Ladicky, J. Shi, M. Pollefeys, Pulling things out of perspective, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2014, pp. 89-96.K. Nathan Silberman, Derek Hoiem, R. Fergus, Indoor segmentation and support inference from rgbd images, in: ECCV, 2012.Liu, J. Yuen, A. Torralba, Sift flow: Dense correspondence across scenes and its applications, IEEE transactions on pattern analysis and machine intelligence 33(5) (2011) 978-994.Konrad, M. Wang, P. Ishwar, 2d-to-3d image conversion by learning depth from examples, in: Computer Vision and Pattern Recognition Workshops (CVPRW), 2012 IEEE Computer Society Conference on, IEEE, 2012, pp. 16-22.Liu, C. Shen, G. Lin, Deep convolutional neural fields for depth estimation from a single image, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 5162-5170.Wang, X. Shen, Z. Lin, S. Cohen, B. Price, A.L. Yuille, Towards unified depth and semantic prediction from a single image, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 2800-2809.Geiger, P. Lenz, C. Stiller, R. Urtasun, Vision meets robotics: The kitti dataset, International Journal of Robotics Research (IJRR).Achanta, S. Süsstrunk, Saliency detection using maximum symmetric surround, in: Image processing (ICIP), 2010 17th IEEE international conference on, IEEE, 2010, pp. 2653-2656.E. Rahtu, J. Kannala, M. Salo, J. Heikkilä, Segmenting salient objects from images and videos, in: Computer Vision-ECCV 2010, Springer, 2010, pp. 366-37.
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Thèses sur le sujet "Hang kong gong ye"

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Lau, Man-chun. « A study of Hong Kong popular music industry (1930-2000) 1930 zhi 2000 nian jian Xianggang liu xing yin yue gong ye de bian qian / ». Click to view the E-thesis via HKUTO, 2003. http://sunzi.lib.hku.hk/hkuto/record/B4389608X.

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Chen, Shengluo. « Zhongguo guo you qi ye de chan quan bian ge yu dang de ling dao = The change of property rights in state-owned enterprises and the party leadership / ». click here to view the abstract and table of contents, 2000. http://net3.hkbu.edu.hk/~libres/cgi-bin/thesisab.pl?pdf=b15941176a.pdf.

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« A corporate finance perspective comparison among HSBC, Hang Seng Bank, and BOCHK ». 2003. http://library.cuhk.edu.hk/record=b5891393.

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Résumé :
by Lam Yu-Kan, Wong Yik.
Thesis (M.B.A.)--Chinese University of Hong Kong, 2003.
Includes bibliographical references (leaf 74).
ABSTRACT --- p.3
TABLE OF CONTENTS --- p.5
Chapter
Chapter 1. --- INTRODUCTION OF THE BANKING INDUSTRY IN HK --- p.6
Chapter 2. --- BRIEF HISTORY AND CORPORATE STRATEGIES (WITH CHANGES OVER THE HISTORY) --- p.7
Chapter 3. --- OPERATING AND FINANCIAL PERFORMANCE EVALUATION ..… --- p.16
Chapter 4. --- LONG-TERM INVESTMENT POTENTIAL --- p.57
Chapter 5. --- CONCLUSIONS AND RECOMMENDATIONS --- p.68
BIBLIOGRAPHY --- p.74
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« From mobilisation to solidarity : a study of the role of non-union labour organisation in labour movement with special reference to the Hong Kong case ». Chinese University of Hong Kong, 1986. http://library.cuhk.edu.hk/record=b5885656.

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« 香港教師團體的國民教育觀 : 教協及教聯的符號學比較分析 ». 2006. http://library.cuhk.edu.hk/record=b5896490.

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Résumé :
李紹宏.
"2006年8月"
論文(哲學碩士)--香港中文大学, 2006.
參考文獻(leaves 243-262).
"2006 nian 8 yue"
Abstracts in Chinese and English.
Li Shaohong.
Lun wen (zhe xue shuo shi)--Xianggang Zhong wen da xue, 2006.
Can kao wen xian (leaves 243-262).
Chapter 第一章: --- 導言 --- p.1
Chapter 1.1 --- 研究背景:香港政治文化與國民教育取向 --- p.2
Chapter 1.2 --- 教師團體 --- p.7
Chapter 1.2.1. --- 教協簡介 --- p.7
Chapter 1.2.2 --- 教聯簡介 --- p.9
Chapter 1.3 --- 過渡期的政治變化與國民教育的關係 --- p.11
Chapter 1.4 --- 回歸前後的國民教育議題論爭 --- p.16
Chapter 1.5 --- 研究意義 --- p.33
Chapter 1.6 --- 章節安排 --- p.34
Chapter 第二章: --- 硏究理論 --- p.36
Chapter 2.1 --- 「民族主義」簡介 --- p.36
Chapter 2.2 --- 「中國」分析-回應西方民族主義理論 --- p.39
Chapter 2.2.1 --- 對「中國」的質疑 --- p.40
Chapter 2.2.2 --- 杜贊奇與葛兆光等理論 --- p.42
Chapter 2.2.3 --- 「文化中國」的認同 --- p.47
Chapter 2.2.4 --- 小結 --- p.49
Chapter 2.3 --- 身份認同 --- p.49
Chapter 2.3.1 --- 有關「身份認同」 --- p.50
Chapter 2.3.2 --- 有關「民族認同」 --- p.51
Chapter 2.4 --- 中國民族主義:對外戰爭與「創傷記憶」的民族意識 --- p.54
Chapter 2.5 --- 「創傷記憶」與「驕傲盛世」回憶的民族主義--中國人身份的回溯 --- p.58
Chapter 第三章: --- 研究設計 --- p.64
Chapter 3.1 --- 硏究問題 --- p.64
Chapter 3.2 --- 硏究起點 --- p.65
Chapter 3.3 --- 硏究對象 --- p.67
Chapter 3.3.1 --- 《教協報》及《香港教育》簡介 --- p.67
Chapter 3.3.2 --- 本硏究的選材及標記 --- p.67
Chapter 3.4 --- 硏究方法 --- p.68
Chapter 3.4.1 --- 質化研究法(Qualitative research) --- p.68
Chapter 3.4.2 --- 符號學分析方法 --- p.69
Chapter 第四章、 --- 神話的建立過程-對外仇恨的民族主義與國民教育(一) --- p.82
Chapter 4.1 --- 引言 --- p.82
Chapter 4.2 --- 教協 --- p.83
Chapter 4.2.1 --- 反日愛國與符號分析 --- p.83
Chapter 4.2.2 --- 反日與國民教育 --- p.89
Chapter 4.3 --- 教聯 --- p.92
Chapter 4.3.1 --- 反日愛國與符號分析 --- p.92
Chapter 4.3.2 --- 反日與國民教育 --- p.94
Chapter 4.4 --- 小結 --- p.96
Chapter 第五章、 --- 神話的建立過程-對外仇恨的民族主義與國民教育(二) --- p.99
Chapter 5.1 --- 引言 --- p.99
Chapter 5.2 --- 教協 --- p.99
Chapter 5.2.1 --- 反日愛國與符號分析 --- p.100
Chapter 5.2.2 --- 反日與國民教育-理性神話 --- p.103
Chapter 5.3 --- 教聯 --- p.107
Chapter 5.3.1 --- 反日愛國與符號分析 --- p.107
Chapter 5.3.2 --- 反曰與國民教育 --- p.108
Chapter 5.4 --- 小結 --- p.109
Chapter 第六章 --- 三個神話的確立 --- p.112
Chapter 6.1 --- 文字及圖片分析 --- p.112
Chapter 6.1.1 --- 系譜軸(Paradigm) --- p.112
Chapter 6.1.2 --- 毗鄰軸(Syntagm) --- p.113
Chapter 6.2 --- 歌曲及語言分析 --- p.118
Chapter 6.2.1 --- 歌曲介紹 --- p.119
Chapter 6.2.2 --- 符號分析 --- p.124
Chapter 6.3 --- 三個神話的建立 --- p.130
Chapter 6.3.1 --- 神話的建構過程 --- p.130
Chapter 6.3.2 --- 神話的延伸 --- p.136
Chapter 6.4 --- 小結 --- p.140
Chapter 第七章: --- 血緣神話認同-八九民運 --- p.144
Chapter 7.1 --- 引言 --- p.144
Chapter 7.2. --- 教協愛國及民主想像 --- p.144
Chapter 7.3. --- 教聯黨國不分的矛盾 --- p.157
Chapter 7.3.1 --- 對中共的批評與隱晦 --- p.159
Chapter 7.3.2 --- 「自我失語」與「失憶」的教聯六四歷史 --- p.164
Chapter 7.3.3 --- 教導六四史的方法--客觀理性的歷史教育還是失憶教育? --- p.166
Chapter 第八章 --- 回蹄神話(一)教聯 --- p.174
Chapter 8.1 --- 引言 --- p.174
Chapter 8.2 --- 民族恥´辱ؤ道德與回歸 --- p.177
Chapter 8.3 --- 奴化教育-救贖與回歸 --- p.186
Chapter 第九章 --- 回歸神話(二)教協 --- p.201
Chapter 9.1 --- 引言 --- p.201
Chapter 9.2 --- 民族恥辱-道德與回歸 --- p.201
Chapter 9.3 --- 回歸矛盾-血緣神話 --- p.205
Chapter 9.4 --- 小結-教聯及教協回歸的取態 --- p.216
Chapter 第十章 --- 結論 --- p.225
Chapter 10.1 --- 總結--回應第一個問題 --- p.225
Chapter 10.2 --- 後現代的質疑 --- p.226
Chapter 10.3 --- 批判與國民教育-回應問題二 --- p.229
Chapter 10.4 --- 研究的起點與啓示-民族身份的反思、教師的反省 --- p.233
Chapter 10.5 --- 硏究的貢獻、限制與啓發 --- p.236
Chapter 10.5.1 --- 硏究的貢獻及特色 --- p.237
Chapter 10.5.2 --- 研究限制 --- p.237
Chapter 10.5.3 --- 未及的討論 --- p.240
Chapter 10.6 --- 後記 --- p.241
參考資料 --- p.243
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Livres sur le sujet "Hang kong gong ye"

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Guo, Liangyu, Jihe Bian et Jineng Shi. Shanghai hang kong gong ye zhi. 8e éd. Shanghai : Shanghai she hui ke xue yuan chu ban she, 1996.

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Zhongguo hang kong gong ye shi bian xiu ban gong shi. Zhongguo hang kong gong ye lao zhao pian. 8e éd. Beijing Shi : Hang kong gong ye chu ban she, 2011.

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Gong, Haiping. Zhongguo min yong hang kong gong ye nian jian. 8e éd. Beijing : Hang kong gong ye chu ban she, 2014.

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shi, Zhongguo hang kong gong ye shi bian xiu ban gong. Zhongguo hang kong gong ye ren wu zhuan : Ling dao pian. 8e éd. Beijing Shi : Beijing hang kong gong ye chu ban she, 2011.

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Zhongguo hang kong gong ye shi bian xiu ban gong shi. Zhongguo hang kong gong ye ren wu zhuan : Zhuan jia pian. 8e éd. Beijing Shi : Beijing hang kong gong ye chu ban she, 2011.

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yu, Miao de. Zhong guo min yong hang kong gong ye jin rong fu wu xi tong yan jiu. Bei jing : Hang kong gong ye chu ban she, 2009.

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Tian zhi wu : Zhongguo hang kong gong ye gao duan fang tan lu. Beijing Shi : Hang kong gong ye chu ban she, 2008.

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Yao, Yuan. Tian zhi wu : Zhongguo hang kong gong ye gao duan fang tan lu. 8e éd. Beijing Shi : Hang kong gong ye chu ban she, 2008.

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Zhou, Rixin. Ji shen pen qi shi dai : Zhongguo hang kong gong ye, 1951-1965. Beijing Shi : Beijing hang kong hang tian da xue chu ban she, 2013.

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Freiberg, Kevin. Wo wei yi kuang : Mei guo xi nan hang kong wei shen me neng cheng gong. 8e éd. Beijing : Zhong guo she hui ke xue chu ban she, 2005.

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