Visual Object Recognition

ImageNet: A large-scale hierarchical image database

Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333

Distinctive Image Features from Scale-Invariant Keypoints

Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589

Histograms of Oriented Gradients for Human Detection

Dalal, N., & Triggs, B. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.177 · Cited by 33,584

Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography

Fischler, M. A., & Bolles, R. C. (1981) · Communications of the ACM · doi:10.1145/358669.358692 · Cited by 25,893

A decision-theoretic generalization of on-line learning and an application to boosting

Freund, Y., & Schapire, R. E. (1997) · Journal of Computer and System Sciences · doi:10.1006/jcss.1997.1504 · Cited by 20,466

The pascal visual object classes (VOC) challenge

Everingham, M., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2010) · International Journal of Computer Vision · doi:10.1007/s11263-009-0275-4 · Cited by 19,599

Rapid object detection using a boosted cascade of simple features

Viola, P., & Jones, M. (2005) · Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001 · doi:10.1109/cvpr.2001.990517 · Cited by 18,300

Normalized cuts and image segmentation

Shi, J., & Malik, J. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.868688 · Cited by 15,935

Robust Real-Time Face Detection

Viola, P., & Jones, M. J. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000013087.49260.fb · Cited by 14,097

Speeded-Up Robust Features (SURF)

Bay, H., Ess, A., Tuytelaars, T., & Van Gool, L. (2008) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2007.09.014 · Cited by 13,557

Learning Richer Features in Deep CNN for Object Detection

Li, Y., He, X., Zheng, Z., & Chen, Y. (2020) · International Conference on Artificial Intelligence and Computer Engineering (ICAICE) · doi:10.1109/icaice51518.2020.00018 · Cited by 1

University of Siegen, Kobe University and Muroran Institute of Technology at TRECVID 2013 Multimedia Event Detection

Shirahama, K., Li, C., Grzegorzek, M., & Uehara, K. (2013) · TRECVID · Cited by 1

Kapitel XI Einsatzrecht Teil II – Übertragung auf die Dehumanisierung der Kriegführung und Ergebnis

Singer, T. (2018) · Springer eBooks · doi:10.1007/978-3-662-57856-8_11 · Cited by 1

Passive Scene Recognition

Meißner, P. (2019) · Springer tracts in advanced robotics · doi:10.1007/978-3-030-31852-9_3 · Cited by 1

Spatio-temporal tracking of vehicles using Deep Learning, applied on aerial videos

Lechgar, H., Malaainine, M. E. I., & Rhinane, H. (2020) · IEEE International Conference of Moroccan Geomatics (MORGEO) · doi:10.1109/morgeo49228.2020.9121907 · Cited by 1

A Survey on Algorithms in Deep Learning

Menon, S. P. (2020) · Advances in computer and electrical engineering book series · doi:10.4018/978-1-7998-2803-7.ch017 · Cited by 1

Understanding a city from its visuals: An interdisciplinary program proposal

Akgül, C. B., Sönmez, N. O., & Alaçam, S. (2017) · Signal Processing and Communications Applications Conference (SIU) · doi:10.1109/siu.2017.7960696 · Cited by 1

Remote Sensing of Mars: Detection of Impact Craters on the Mars Global Surveyor DTM by Integrating Edge- and Region-Based Algorithms

Athanassas, C. D., Vaiopoulos, A. D., Kolokoussis, P., & Argialas, D. P. (2018) · Earth Moon and Planets · doi:10.1007/s11038-018-9515-3 · Cited by 1

Exploiting label semantic relatedness for unsupervised image annotation with large free vocabularies

Pellegrin, L., Escalante, H. J., Montes-y-Gómez, M., & Gonzalez, F. A. (2019) · Multimedia Tools and Applications · doi:10.1007/s11042-019-7357-2 · Cited by 1

Automatic Handgun Detection in X-ray Images using Bag of Words Model with Selective SearchPreprint

Piñol, D. C., & Reyes, E. J. M. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1903.01322 · Cited by 1

Measuring visual vocabulary appropriateness by dispersion index and its improvement by globalizing SIFT descriptors

Suzuki, I. (2014) · IEEE International Symposium on Computational Intelligence and Informatics (CINTI) · doi:10.1109/cinti.2014.7028672

Modelos de representación de características para la clasificación de acciones humanas en video: estado del arte

Hernández-García, R., García-Reyes, E. B., Cózar, J. R., & Guil, N. (2014) · DOAJ (DOAJ: Directory of Open Access Journals)

Mobile Augmented Reality for Information Surfaces

Grubert, J. (2015) · doi:10.13140/rg.2.1.2999.8802

Multimodal Fusion for Combining Textual and Visual Information in a Semantic Model

Tran, N. K. (2012)

Multi-view near-InfrarediImage mosaicking for face detection in smart cities

M., S. K. K., Panetta, K. A., & Agaian, S. С. (2018) · Mobile Multimedia/Image Processing, Security, and Applications · doi:10.1117/12.2305011

Edge Detection for Pattern Recognition: A SurveyPreprint

James, A. P. (2016) · arXiv (Cornell University) · doi:10.13140/rg.2.1.1965.2888

Classical Algorithm vs. Machine Learning in Objects Recognition

Czygier, J., Tomaszuk, P., Łukowska, A., Pawel, S., & Dzierżek, K. (2019) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-17798-0_58

An Efficient Replay Method to Prevent SURF-Based Face Detection

Dadkhah, S., Köppen, M., Sadeghi, S., & Yoshida, K. (2018) · Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE) · doi:10.1109/apwconcse.2018.00012

The Determination of Distances between Images by de Rham Currents Method

Chukanov, S. N. (2020) · Modeling and Analysis of Information Systems · doi:10.18255/1818-1015-2020-1-96-107

Object Attribute Recognition Based on Hard Negative Mining and Convolutional Neural Network

Lei, M., & Liu, F. (2020) · Smart innovation, systems and technologies · doi:10.1007/978-981-15-3863-6_14

Computer Vision Concepts and Applications

O’Brien, B., & Uma, V. (2021) · CRC Press eBooks · doi:10.1201/9781003005629-6

Visual recognition incorporating features of self-supervised models for the use of unlabelled data

Díaz, G., Nicolis, O., & Peralta, B. (2021) · IEEE International Conference on Automatica · doi:10.1109/icaacca51523.2021.9465233

Bi-shifting semantic auto-encoder for zero-shot learning

Wang, Y. (2021) · Electronic Research Archive · doi:10.3934/era.2022008

Introduction

Meißner, P. (2019) · Springer tracts in advanced robotics · doi:10.1007/978-3-030-31852-9_1

Related Work

Meißner, P. (2019) · Springer tracts in advanced robotics · doi:10.1007/978-3-030-31852-9_2

Designing and evaluating a system for the effective analysis of sign language video content for the improvement of video quality

Moscatiello, J. (2021) · doi:10.32920/ryerson.14652186

Algorithms and representations for visual recognition

Malik, J., & Maji, S. (2011)

Efficient Visual Recognition

Liu, L., Pietikäinen, M., Qin, J., Ouyang, W., & Gool, L. V. (2020) · International Journal of Computer Vision · doi:10.1007/s11263-020-01351-w · Cited by 5

Object Categorization

Pinz, A. J. (2005) · Foundations and Trends® in Computer Graphics and Vision · doi:10.1561/0600000003 · Cited by 84

Research Statement Computer Vision — Visual Recognition

Berg, A. C. (2013)

Other Considerations and Current Challenges

Grauman, K. L., & Leibe, B. (2011) · Synthesis lectures on artificial intelligence and machine learning · doi:10.1007/978-3-031-01553-3_12