Image Classification with the Fisher Vector: Theory and Practice

ImageNet classification with deep convolutional neural networks

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ImageNet: A large-scale hierarchical image database

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Distinctive Image Features from Scale-Invariant Keypoints

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The pascal visual object classes (VOC) challenge

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Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories

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The Pascal Visual Object Classes Challenge: A Retrospective

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Video Google: a text retrieval approach to object matching in videos

Sivic, & Zisserman (2003) · Proceedings Ninth IEEE International Conference on Computer Vision · doi:10.1109/iccv.2003.1238663 · Cited by 6,367

Visual categorization with bags of keypoints

Csurka, G. (2004) · Cited by 4,379

SUN database: Large-scale scene recognition from abbey to zoo

Xiao, J., Hays, J., Ehinger, K. A., Oliva, A., & Torralba, A. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2010.5539970 · Cited by 3,283

Locality-constrained Linear Coding for image classification

Wang, J., Yang, J., Yu, K., Lv, F., Huang, T., & Gong, Y. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2010.5540018 · Cited by 3,100

Characterizing objects with SIKA features for multiclass classification

Srivastava, S., Mukherjee, P., & Lall, B. (2015) · Applied Soft Computing · doi:10.1016/j.asoc.2015.12.014 · Cited by 9

A two-step approach to describing web topics via probable keywords and prototype images from background-removed similarities

Pang, J., Tao, F., Li, L., Huang, Q., Yin, B., & Tian, Q. (2017) · Neurocomputing · doi:10.1016/j.neucom.2017.08.057 · Cited by 9

Drought Stress Classification Using 3D Plant Models

Srivastava, S., Bhugra, S., Lall, B., & Chaudhury, S. (2017) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2017.240 · Cited by 9

Recognizing Actions in Wearable-Camera Videos by Training Classifiers on Fixed-Camera Videos

Mi, Y., Zheng, K., & Wang, S. (2018) · International Conference on Multimedia Retrieval · doi:10.1145/3206025.3206041 · Cited by 8

Explorations on visual localization from active to passive

Yang, Y., Wu, Y., & Chen, N. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-018-6347-0 · Cited by 9

Part-Level Sketch Segmentation and Labeling Using Dual-CNN

Zhu, X., Xiao, Y., & Zheng, Y. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-04167-0_34 · Cited by 9

Robust Acoustic Event Classification using Fusion Fisher Vector features

Mulimani, M., & Koolagudi, S. G. (2019) · Applied Acoustics · doi:10.1016/j.apacoust.2019.05.020 · Cited by 9

Automated characterization and classification of coronary atherosclerotic plaques for intravascular optical coherence tomography

Yang, J., Zhang, B., Wang, H., Lin, F., Han, Y., & Liu, X. (2019) · Journal of Applied Biomedicine · doi:10.1016/j.bbe.2019.06.006 · Cited by 9

Learning semantic dependencies with channel correlation for multi-label classification

Xue, L., Jiang, D., Wang, R., Yang, J., & Hu, M. Q. (2019) · The Visual Computer · doi:10.1007/s00371-019-01731-5 · Cited by 9

Compact Interchannel Sampling Difference Descriptor for Color Texture Classification

Dong, Y., Jin, M., Li, X., Ma, J., Liu, Z., Wang, L., & Zheng, L. (2020) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2020.3014526 · Cited by 9

Predicting a Cold from Speech Using Fisher Vectors; SVM and XGBoost as Classifiers

Egas-López, J. V., & Gosztolya, G. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-60276-5_15 · Cited by 9

High-Resolution SAR Image Classification via Multiscale Local Fisher Patterns

Zhao, Z., Jia, M., & Wang, L. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.3039847 · Cited by 9

Deep convolutional neural network for preliminary in-field classification of lichen species

Galanty, A., Danel, T., Węgrzyn, M. H., Podolak, I., & Podolak, I. T. (2021) · Biosystems Engineering · doi:10.1016/j.biosystemseng.2021.01.004 · Cited by 11

Recognition of varying size scene images using semantic analysis of deep activation maps

Gupta, S., Dileep, A. D., & Thenkanidiyoor, V. (2021) · Machine Vision and Applications · doi:10.1007/s00138-021-01168-8 · Cited by 9

Reliable shot identification for complex event detection via visual-semantic embedding

Luo, M., Chang, X., & Gong, C. (2021) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2021.103300 · Cited by 9

Soft-labeling approach along with an ensemble of models for predicting subjective freshness of spinach leaves

Koyama, K., & Lyu, S. (2021) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2021.106633 · Cited by 9

A Parallel Convolution and Decision Fusion-Based Flower Classification Method

Jia, L., Zhai, H., Yuan, X., Jiang, Y. L., & Ding, J. (2022) · Mathematics · doi:10.3390/math10152767 · Cited by 11

Towards optimal VLAD for human action recognition from still images

Zhang, L., Li, C., Peng, P., Xiang, X., & Song, J. (2016) · Image and Vision Computing · doi:10.1016/j.imavis.2016.03.002 · Cited by 9

Categorizing plant images at the variety level: Did you say fine-grained?

Champ, J., Lorieul, T., Bonnet, P., Maghnaoui, N., Sereno, C., Dessup, T., Boursiquot, J., Audeguin, L., Lacombe, T., & Joly, A. (2016) · Pattern Recognition Letters · doi:10.1016/j.patrec.2016.05.022 · Cited by 9

Learned features versus engineered features for multimedia indexing

Budnik, M., Gutiérrez-Gómez, L., Safadi, B., Pellerin, D., & Quenot, G. M. (2016) · Multimedia Tools and Applications · doi:10.1007/s11042-016-4240-2 · Cited by 10

A Quantitative Assessment of Image Normalization for Classifying Histopathological Tissue of the Kidney

Gadermayr, M., Cooper, S. S., Klinkhammer, B. M., Boor, P., & Merhof, D. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66709-6_1 · Cited by 9

Image classification method rationally utilizing spatial information of the image

Wu, C., Li, Y., Zhao, Z., & Liu, B. (2019) · Multimedia Tools and Applications · doi:10.1007/s11042-019-7254-8 · Cited by 9

A BLSTM with Attention Network for Predicting Acute Myeloid Leukemia Patient’s Prognosis using Comprehensive Clinical Parameters

Lu, C.-C., Li, J.-L., Wang, Y., Ko, B., Tang, J., & Lee, C.-C. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8856524 · Cited by 9

Self-Learning Camera: Autonomous Adaptation of Object Detectors to Unlabeled Video StreamsPreprint

Gaidon, A., Zen, G., & Rodríguez-Serrano, J. A. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1406.4296 · Cited by 9

Computer-Aided Colorectal Tumor Classification in NBI Endoscopy Using CNN FeaturesPreprint

Tamaki, T., Sonoyama, S., Hirakawa, T., Raytchev, B., Kaneda, K., Koide, T., Yoshida, S., Mieno, H., & Tanaka, S. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1608.06709 · Cited by 10

Automatic grading of placental maturity based on LIOP and fisher vector

Lei, B., Li, X., Yao, Y., Li, S., Chen, S., Zhou, Y., Ni, D., & Wang, T. (2014) · 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society · doi:10.1109/embc.2014.6944666 · Cited by 8

Imbalanced Multi-instance Multi-label Learning via Coding Ensemble and Adaptive Thresholds

Zhang, X., Luo, T., Liu, Y.-X., & Hou, C. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3680911 · Cited by 8

Object Classification using Ensemble of Local and Deep Features

Srivastava, S., Mukherjee, P., Lall, B., & Jaiswal, K. (2017) · International Conference on Advances in Pattern Recognition · doi:10.1109/icapr.2017.8593056 · Cited by 8

Adaptive Superpixel Segmentation with Fisher Vectors for Ship Detection in SAR Images

Wang, X., Li, G., & Plaza, A. (2020) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss39084.2020.9323433 · Cited by 8

MRDA-MGFSNet: Network Based on a Multi-Rate Dilated Attention Mechanism and Multi-Granularity Feature Sharer for Image-Based Butterflies Fine-Grained Classification

Li, M., Zhou, G., Cai, W., Li, J., Li, M., He, M., Hu, Y., & Li, L. (2021) · Symmetry · doi:10.3390/sym13081351 · Cited by 8

Translating Braille into Chinese based on improved CBHG model

Huang, T., Su, W., Liu, L., Zhang, J., Cai, C., Yuan, Y., & Xu, C. (2023) · Displays · doi:10.1016/j.displa.2023.102445 · Cited by 9

Depression Detection with Dynamic and Static Visual Features

Wang, Y., & Li, Z. (2023) · Journal of Circuits Systems and Computers · doi:10.1142/s0218126623503115 · Cited by 8

Indoor Scene Recognition: An Attention-Based Approach Using Feature Selection-Based Transfer Learning and Deep Liquid State Machine

Surendran, R., Chihi, I., Anitha, J., & Hemanth, D. J. (2023) · Algorithms · doi:10.3390/a16090430 · Cited by 9

An enhanced ResNet deep learning method for multimodal signal-based locomotion intention recognition

Sun, H., Gu, X., Zhang, Y., Sun, F., Zhang, S., Wang, D., & Yu, H. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.107254 · Cited by 9

A Review of Human Action Recognition Based On Deep Learning

Jiang, Z., & Liu, Y. (2024) · International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) · doi:10.1109/iciibms62405.2024.10792697 · Cited by 8

Fisher Encoding of Adaptive Fast Persistent Feature Histograms for Partial Retrieval of 3D Pottery Objects

Savelonas, M. A., Pratikakis, I., & Sfikas, K. (2014) · Eurographics Workshop on 3D Object Retrieval · doi:10.2312/3dor.20141051 · Cited by 8

Joint Recognition and Segmentation of Actions via Probabilistic Integration of Spatio-Temporal Fisher Vectors

Carvajal, J., McCool, C., Lovell, B. C., & Sanderson, C. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-42996-0_10 · Cited by 8

Hierarchical Late Fusion for Concept Detection in Videos

Strat, S. T., Benoît, A., Lambert, P., Bredin, H., & Quenot, G. M. (2014) · Advances in computer vision and pattern recognition · doi:10.1007/978-3-319-05696-8_3 · Cited by 9

Spectral attribute learning for visual regression

Chen, K., Jia, K., Zhang, Z., & Kämäräinen, J. (2017) · Pattern Recognition · doi:10.1016/j.patcog.2017.01.009 · Cited by 8

Image classification with CNN-based Fisher vector coding

Song, Y., Hong, X., McLoughlin, I. V., & Dai, L.-R. (2016) · Visual Communications and Image Processing · doi:10.1109/vcip.2016.7805494 · Cited by 8

Local feature representation based on linear filtering with feature pooling and divisive normalization for remote sensing image classification

Wan, L., Liu‎, N., Guo, Y., Huo, H., & Fang, T. (2017) · Journal of Applied Remote Sensing · doi:10.1117/1.jrs.11.016017 · Cited by 8

Fisher Vectors for PolSAR Image Classification

Redolfi, J. A., Sánchez, J., & Flesia, A. G. (2017) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2017.2750800 · Cited by 8

Fusing Geometry and Appearance for Road Segmentation

Cheng, G., Qian, Y., & Elder, J. H. (2017) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2017.28 · Cited by 8

Flip-Invariant Motion Representation

Kobayashi, T. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.600 · Cited by 8

Codebook-Free Compact Descriptor for Scalable Visual Search

Wu, Y., Gao, F., Huang, Y., Lin, J., Chandrasekhar, V., Yuan, J., & Duan, L. (2018) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2018.2856628 · Cited by 8

Fisher Vector Encoding of Supervoxel-Based Features for Airborne LiDAR Data Classification

Akwensi, P. H., Kang, Z., & Yang, J. (2019) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2019.2922308 · Cited by 8

Learning second-order statistics for place recognition based on robust covariance estimation of CNN features

Zhang, W., Yan, Z., Wang, Q., Wu, X., & Zuo, W. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.02.001 · Cited by 8

Describing Textures Using Natural Language

Wu, C., Timm, M., & Maji, S. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58452-8_4 · Cited by 9

PRIMAL-GMM: PaRametrIc MAnifold Learning of Gaussian Mixture Models

Liu, Z., Yu, L., Hsiao, J. H., & Chan, A. B. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.3048727 · Cited by 8

Local Coding Based Matching Kernel Method for Image Classification

Song, Y., McLoughlin, I. V., & Dai, L.-R. (2014) · PLoS ONE · doi:10.1371/journal.pone.0103575 · Cited by 8

Fine-grained visual categorization with fine-tuned segmentation

Li, L., Guo, Y., Xie, L., Kong, X., & Tian, Q. (2015) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2015.7351156 · Cited by 8

Realistic human action recognition: When deep learning meets VLAD

Lei Zhang, A., Feng, Y., Han, J., & Zhen, X. (2016) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2016.7471897 · Cited by 8

A New Probabilistic Representation of Color Image Pixels and Its Applications

Lin, Z., Qin, H., & Chan, S. C. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2883580 · Cited by 8

Texture-based analysis of hydrographical basins with multispectral imagery

Bascoy, P. G., Garea, A. S., Heras, D. B., Argüello, F., & Ordóñez, Á. (2019) · SPIE Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology · doi:10.1117/12.2532760 · Cited by 8

Ground Truth Data, Content, Metrics, and Analysis

Krig, S. (2016) · Springer eBooks · doi:10.1007/978-3-319-33762-3_7 · Cited by 8

HEp-2 Cell Classification via Fusing Texture and Shape InformationPreprint

Qi, X., Zhao, G., Li, C.-G., Guo, J. H., & Pietikäinen, M. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1502.04658 · Cited by 8

A survey on Kornia: an Open Source Differentiable Computer Vision Library for PyTorchPreprint

Riba, E., Mishkin, D., Shi, J., Ponsa, D., Moreno-Noguer, F., & Bradski, G. R. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2009.10521 · Cited by 12

Contrastive Reasoning in Neural NetworksPreprint

Prabhushankar, M., & AlRegib, G. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.12329 · Cited by 12

Fine-Grained Image Analysis with Deep Learning: A SurveyPreprint

Wei, X.-S., Song, Y.-Z., Aodha, O. M., Wu, J., Peng, Y., Tang, J., Yang, J. J., & Belongie, S. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.06119 · Cited by 8

HEp-2 Cell Classification via Combining Multiresolution Co-Occurrence Texture and Large Region Shape Information

Qi, X., Zhao, G., Li, C.-G., Guo, J. H., & Pietikäinen, M. (2015) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2015.2508938 · Cited by 7

Recognition of Group Activities in Videos Based on Single-and Two-Person Descriptors

Lathuilière, S., Evangelidis, G., & Horaud, R. (2017) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2017.31 · Cited by 7

HOFA-Net: A High-Order Feature Association Network for Dense Object Detection in Remote Sensing

Xu, Y., Wu, X., Wang, L., Xu, L., Shao, Z., & Fei, A. (2023) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2023.3335288 · Cited by 7

Feature Engineering Versus Deep Learning for Scene Recognition: A Brief Survey

Susan, S., & Tuteja, M. (2024) · International Journal of Image and Graphics · doi:10.1142/s0219467825500548 · Cited by 7

Target Detection Based on Regional Feature Difference in Synthetic Aperture Interferometric Radiometer

Fang, B., Zhu, D., Hu, F., Xu, Y., Hao, Y., Chen, X., Tao, J., Min, J., & Zheng, B. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3566250 · Cited by 7

1Learning Non-linear SVM in Input Space for Image Classification

Sharma, G., Jurie, F., & Pérez, P. (2014) · Cited by 7

Structured Feature Similarity with Explicit Feature Map

Kobayashi, T. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.136 · Cited by 7

High-Order Local Pooling and Encoding Gaussians Over a Dictionary of Gaussians

Li, P., Zeng, H., Wang, Q., Shiu, S., & Lei Zhang, A. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2695884 · Cited by 7

Key Joints Selection and Spatiotemporal Mining for Skeleton-Based Action Recognition

Wang, Z., Zhang, C., Luo, W., & Lin, W. (2018) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2018.8451483 · Cited by 7

Comparison of HOG and Fisherfaces Based Face Recognition System Using MATLAB

Reddy, N. V. M. C., & Kumar, K. (2021) · International Conference for Emerging Technology (INCET) · doi:10.1109/incet51464.2021.9456366 · Cited by 7

Blind image quality assessment with channel attention based deep residual network and extended LargeVis dimensionality reduction

Han, H., Li, Z., Li, J., Zhang, J., & Wang, M. (2021) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2021.103296 · Cited by 7

A fisher score-based multi-instance learning method assisted by mixture of factor analysis

Huang, S., Liu, Z., Jin, W., & Mu, Y. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.07.075 · Cited by 7

Box Supervised Video Segmentation Proposal Network

Hannan, T., Koner, R., Kobold, J., & Schubert, M. (2022) · International Machine Vision and Image Processing Conference (IMVIP) · doi:10.56541/azwk8552 · Cited by 11

Semantic-aware visual scene representation

Parseh, M. J., Rahmanimanesh, M., Keshavarzi, P., & Azimifar, Z. (2022) · International Journal of Multimedia Information Retrieval · doi:10.1007/s13735-022-00246-5 · Cited by 7

The 2013 SESAME Multimedia Event Detection and Recounting System

Bolles, R. C., Burns, J. B., Herson, J. A., Myers, G. K., Pancoast, S., van Hout, J., Wong, J., Wong, J., Yeh, E., Habibian, A., et al. (2013) · TRECVID · Cited by 7

Novel general KNN classifier and general nearest mean classifier for visual classification

Liu, Q., Puthenputhussery, A., & Liu, C. (2015) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2015.7351113 · Cited by 7

Clustering of hierarchical image database to reduce inter-and intra-semantic gaps in visual space for finding specific image semantics

Pandey, S., Khanna, P., & Yokota, H. (2016) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2016.04.013 · Cited by 7

Bloom Filters and Compact Hash Codes for Efficient and Distributed Image Retrieval

Salvi, A., Ercoli, S., Bertini, M., & Bimbo, A. D. (2016) · IEEE International Symposium on Multimedia (ISM) · doi:10.1109/ism.2016.0113 · Cited by 7

An image classification method that considers privacy-preservation

Liu, C., Shang, Z., & Tang, Y. Y. (2016) · Neurocomputing · doi:10.1016/j.neucom.2016.04.056 · Cited by 7

Saliency-context two-stream convnets for action recognition

Chen, Q.-Q., Liu, F., Li, X., Liu, B., & Zhang, Y. (2016) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2016.7532925 · Cited by 7

A deep sparse coding method for fine-grained visual categorization

Guo, L., & Guo, C. (2016) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2016.7727259 · Cited by 7

CTC Network with Statistical Language Modeling for Action Sequence Recognition in Videos

Lin, M., Inoue, N., & Shinoda, K. (2017) · Thematic Workshops of ACM Multimedia · doi:10.1145/3126686.3126755 · Cited by 7

Hands-on: deformable pose and motion models for spatiotemporal localization of fine-grained dyadic interactions

van Gemeren, C., Poppe, R. W., & Veltkamp, R. C. (2018) · EURASIP Journal on Image and Video Processing · doi:10.1186/s13640-018-0255-0 · Cited by 7

Local Patch Vectors Encoded by Fisher Vectors for Image Classification

Chen, S., Liu, H., Zeng, X., Qian, S., Wei, W., Wu, G., & Duan, B. (2018) · Information · doi:10.3390/info9020038 · Cited by 7

Curvature-based spectral signatures for non-rigid shape retrieval

Limberger, F. A., & Wilson, R. C. (2018) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2018.04.002 · Cited by 7

Temporal Aggregation of Visual Features for Large-Scale Image-to-Video Retrieval

García, N. (2018) · International Conference on Multimedia Retrieval · doi:10.1145/3206025.3206083 · Cited by 8

Using a generic model for codebook-based gait recognition algorithms

Khan, M. H., Farid, M. S., & Grzegorzek, M. (2018) · International Workshop on Biometrics and Forensics (IWBF) · doi:10.1109/iwbf.2018.8401551 · Cited by 7

Isolated sign language recognition with fast hand descriptors

Özdemir, O., Kındıroğlu, A. A., & Akarun, L. (2018) · Signal Processing and Communications Applications Conference (SIU) · doi:10.1109/siu.2018.8404374 · Cited by 7

Violence Detection Based on Spatio-Temporal Feature and Fisher Vector

Cai, H., Jiang, H., Huang, X., Yang, J., & He, X. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-03398-9_16 · Cited by 7

Hierarchical Gaussian descriptor based on local pooling for action recognition

Nguyen, X. S., Mouaddib, A., & Nguyễn, T. P. (2018) · Machine Vision and Applications · doi:10.1007/s00138-018-0989-9 · Cited by 7

Analyzing temporal dynamics of cell deformation and intracellular movement with video feature aggregation

Pang, F., & Liu, Z. (2019) · BioMedical Engineering OnLine · doi:10.1186/s12938-019-0638-1 · Cited by 7

Modelling attention control using a convolutional neural network designed after the ventral visual pathway

Yu, C.-P., Liu, H., Samaras, D., & Zelinsky, G. J. (2019) · Visual Cognition · doi:10.1080/13506285.2019.1661927 · Cited by 6

Optimized feature space learning for generating efficient binary codes for image retrieval

Jose, A., Ottlik, E. S., Rohlfing, C., & Ohm, J.-R. (2021) · Signal Processing Image Communication · doi:10.1016/j.image.2021.116529 · Cited by 7

Predictive digitisation of cultural heritage objects

Pratikakis, I., Savelonas, M. A., Mavridis, P., Παπαϊωάννου, Γ., Sfikas, K., Arnaoutoglou, F., & Rieke‐Zapp, D. H. (2017) · Multimedia Tools and Applications · doi:10.1007/s11042-017-4928-y · Cited by 7

Weighted score-level feature fusion based on Dempster–Shafer evidence theory for action recognition

Zhang, G., Jia, S., Li, X., & Zhang, X. (2018) · Journal of Electronic Imaging · doi:10.1117/1.jei.27.1.013021 · Cited by 7

Cross- View Gait Recognition Using Non-Linear View Transformations of Spatiotemporal Features

Khan, M. H., Farid, M. S., Zahoor, M., & Grzegorzek, M. (2018) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2018.8451629 · Cited by 7

Classification of Melanoma Images with Fisher Vectors and Deep Learning

Liberman, G., Acevedo, D. G., & Mejail, M. E. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-13469-3_85 · Cited by 6

End-to-end Language Identification using NetFV and NetVLAD

Chen, J., Cai, W., Cai, D., Cai, Z., Zhong, H., & Li, M. (2018) · International Symposium on Chinese Spoken Language Processing (ISCSLP) · doi:10.1109/iscslp.2018.8706687 · Cited by 9

UC Merced Submission to the ActivityNet Challenge 2016Preprint

Zhu, Y., Newsam, S. D., & Xu, Z. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1704.03503 · Cited by 7

Approximation and Learning with Deep Convolutional Models: a Kernel PerspectivePreprint

Bietti, A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2102.10032 · Cited by 7

24th Irish Machine Vision and Image Processing Conference

(2022) · doi:10.56541/iprcs_imvip2022 · Cited by 7

Author manuscript, published in "International Journal of Computer Vision (2013)" International Journal of Computer Vision manuscript No. (will be inserted by the editor) Image Classification with the Fisher Vector: Theory and Practice

Sánchez, J., Perronnin, F., Mensink, T., & Verbeek, J. J. (2013)

International Journal of Computer Vision manuscript No. (will be inserted by the editor) Image Classification with the Fisher Vector: Theory and Practice

Sánchez, J., Perronnin, F., Mensink, T., & Verbeek, J. J. (2014)

and Practice

Sánchez, J., Perronnin, F., Mensink, T., Verbeek, J. J., Sánchez, J., & Perronnin, F. (2014)

Local Patch Vectors Encoded by Fisher Vectors for Image Classification

Chen, S., Liu, H., Zeng, X., Qian, S., Wei, W., Wu, G., & Duan, B. (2018) · Information · doi:10.3390/info9020038 · Cited by 7

Fisher Vectors: Beyond Bag-of-Visual-Words Image Representations

Csurka, G., & Perronnin, F. (2011) · Communications in computer and information science · doi:10.1007/978-3-642-25382-9_2 · Cited by 65