SIGNATURE VERIFICATION USING A “SIAMESE” TIME DELAY NEURAL NETWORK

Pattern classification and scene analysis

Duda, R. O., & Hart, P. E. (1973) · CERN Document Server (European Organization for Nuclear Research) · Cited by 12,895 · see citing works

Generalization and network design strategies

LeCun, Y. (1989) · Cited by 885 · see citing works

Neural Networks for Fingerprint Recognition

Baldi, P., & Chauvin, Y. (1993) · Neural Computation · doi:10.1162/neco.1993.5.3.402 · Cited by 171 · see citing works

Automatic Signature Verification Based on Accelerometry

Herbst, N. M., & Liu, C. N. (1977) · IBM Journal of Research and Development · doi:10.1147/rd.213.0245 · Cited by 108 · see citing works

A time delay neural network architecture for speech recognition

Lang, K. (1989) · Cited by 76 · see citing works

Signature verification from position, velocity and acceleration signals: a comparative study

Réjean Plamondon, B., & Parizeau, M. (2003) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.1988.28218 · Cited by 54 · see citing works

DYNAMIC APPROACHES TO HANDWRITTEN SIGNATURE VERIFICATION

Lorette, G., & Réjean Plamondon, B. (1990) · WORLD SCIENTIFIC eBooks · doi:10.1142/9789814439329_0002 · Cited by 26 · see citing works

A time delay neural network character recognizer for a touch terminal

Guyon, I., Albrecht, P., LeCun, Y., et al. (1990) · Cited by 8 · see citing works

Deep learning in neural networks: an overview

Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570 · see citing works

3D Convolutional Neural Networks for Human Action Recognition

Ji, S., Xu, W., Yang, M., & Yu, K. (2012) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.59 · Cited by 6,222 · see citing works

Dimensionality Reduction by Learning an Invariant Mapping

Hadsell, R., Chopra, S., & LeCun, Y. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) · doi:10.1109/cvpr.2006.100 · Cited by 5,336 · see citing works

Fully-Convolutional Siamese Networks for Object Tracking

Bertinetto, L., Valmadre, J., Henriques, J. F., Vedaldi, A., & Torr, P. H. S. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-48881-3_56 · Cited by 4,546 · see citing works

Siamese Neural Networks for One-shot Image Recognition

Koch, G. E., Zemel, R. S., & Salakhutdinov, R. (2015) · Cited by 3,712 · see citing works

Exploring Simple Siamese Representation Learning

Chen, X., & He, K. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.01549 · Cited by 3,725 · see citing works

Dense passage retrieval for open-domain question answering

Karpukhin, V., Oguz, B., Min, S., Lewis, P., Wu, L., Edunov, S., Chen, D., & Yih, W.-T. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.550 · Cited by 3,575 · see citing works

Generalizing from a Few Examples: A Survey on Few-shot Learning

Wang, Y., Yao, Q., Kwok, J. T., & Ni, L. M. (2021) · ACM Computing Surveys · doi:10.1145/3386252 · Cited by 3,165 · see citing works

Learning to rank using gradient descent

Burges, C., Shaked, T., Renshaw, E., Lazier, A., Deeds, M., Hamilton, N., & Hullender, G. (2005) · Proceedings of the 22nd international conference on Machine learning - ICML '05 · doi:10.1145/1102351.1102363 · Cited by 2,836 · see citing works

Learning a Similarity Metric Discriminatively, with Application to Face Verification

Chopra, S., Hadsell, R., & LeCun, Y. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.202 · Cited by 4,036 · see citing works

Deep learning in remote sensing applications: A meta-analysis and review

Ma, L., Liu, Y., Zhang, X., Ye, Y., Yin, G., & Johnson, B. A. (2019) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2019.04.015 · Cited by 2,456 · see citing works

An overview of deep learning in medical imaging focusing on MRI

Lundervold, A. S., & Lundervold, A. (2019) · Zeitschrift für Medizinische Physik · doi:10.1016/j.zemedi.2018.11.002 · Cited by 2,058 · see citing works

Deep Learning Face Representation from Predicting 10,000 Classes

Sun, Y. J., Wang, X., & Tang, X. (2014) · 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.2014.244 · Cited by 1,995 · see citing works

Fully Convolutional Siamese Networks for Change Detection

Daudt, R. C., Saux, B. L., & Boulch, A. (2018) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2018.8451652 · Cited by 1,872 · see citing works

Deep Metric Learning via Lifted Structured Feature Embedding

Song, H. O., Yu, X., Jegelka, S., & Savarese, S. (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.2016.434 · Cited by 1,687 · see citing works

Learning to compare image patches via convolutional neural networks

Zagoruyko, S., & Nikos Komodakis, A. (2015) · 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.2015.7299064 · Cited by 1,540 · see citing works

An Empirical Study of Training Self-Supervised Vision Transformers

Chen, X., Xie, S., & He, K. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00950 · Cited by 1,648 · see citing works

A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images

Zhang, C., Yue, P., Tapete, D., Jiang, L., Shangguan, B., Huang, L., & Liu, G. (2020) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2020.06.003 · Cited by 1,235 · see citing works

Deep multi-scale video prediction beyond mean square errorPreprint

Mathieu, M., Couprie, C., & LeCun, Y. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1511.05440 · Cited by 1,182 · see citing works

Visual Place Recognition: A Survey

Lowry, S., Sünderhauf, N., Newman, P., Leonard, J. J., Cox, D., Corke, P., & Milford, M. J. (2016) · IEEE Transactions on Robotics · doi:10.1109/tro.2015.2496823 · Cited by 1,079 · see citing works

Stereo Matching by Training a Convolutional Neural Network to Compare Image PatchesPreprint

ŽbontarJure, & LeCunYann (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1510.05970 · Cited by 1,009 · see citing works

Person Re-identification: Past, Present and FuturePreprint

Zheng, L., Yang, Y., & Hauptmann, A. G. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1610.02984 · Cited by 977 · see citing works

Deep Learning Algorithms for Bearing Fault Diagnostics—A Comprehensive Review

Zhang, S., Zhang, S., Wang, B., & Habetler, T. G. (2020) · IEEE Access · doi:10.1109/access.2020.2972859 · Cited by 964 · see citing works

A Discriminatively Learned CNN Embedding for Person Reidentification

Zheng, Z., Zheng, L., & Yang, Y. (2017) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3159171 · Cited by 883 · see citing works

Contrastive Representation Learning: A Framework and Review

Le-Khac, P. H., Healy, G., & Smeaton, A. F. (2020) · IEEE Access · doi:10.1109/access.2020.3031549 · Cited by 862 · see citing works

Learning Structured Embeddings of Knowledge Bases

Bordes, A., Weston, J., Collobert, R., & Bengio, Y. (2011) · AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) · doi:10.1609/aaai.v25i1.7917 · Cited by 849 · see citing works

MatchNet: Unifying feature and metric learning for patch-based matching

Han, X., Leung, T., Jia, Y., Sukthankar, R., & Berg, A. C. (2015) · 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.2015.7298948 · Cited by 844 · see citing works

Let there be color!

Iizuka, S., Simo‐Serra, E., & Ishikawa, H. (2016) · ACM Transactions on Graphics · doi:10.1145/2897824.2925974 · Cited by 816 · see citing works

Discriminative Learning of Deep Convolutional Feature Point Descriptors

Simo‐Serra, E., Trulls, E., Ferraz, L., Kokkinos, I., Fua, P., & Moreno-Noguer, F. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.22 · Cited by 804 · see citing works

A Tutorial on Energy-Based Learning

LeCun, Y., Chopra, S., Hadsell, R. T., Ranzato, A., & Huang, F. J. (2006) · Cited by 812 · see citing works

A Survey of Optimization Methods From a Machine Learning Perspective

Sun, S., Cao, Z., Han, Z., & Zhao, J. (2019) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2019.2950779 · Cited by 812 · see citing works

Generalizing from a Few Examples: A Survey on Few-Shot LearningPreprint

Wang, Y., Yao, Q., Kwok, J. T.-Y., & Ni, L. M.-S. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.05046 · Cited by 773 · see citing works

Semantic Parsing via Staged Query Graph Generation: Question Answering with Knowledge Base

Yih, W.-T., Chang, M.-W., He, X., & Gao, J. (2015) · doi:10.3115/v1/p15-1128 · Cited by 769 · see citing works

Bilateral Multi-Perspective Matching for Natural Language Sentences

Wang, Z., Hamza, W., & Florian, R. (2017) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2017/579 · Cited by 751 · see citing works

Gated Siamese Convolutional Neural Network Architecture for Human Re-identification

Varior, R. R., Haloi, M., & Wang, G. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46484-8_48 · Cited by 745 · see citing works

Siamese Neural Networks: An Overview

Chicco, D. (2020) · Methods in molecular biology · doi:10.1007/978-1-0716-0826-5_3 · Cited by 681 · see citing works

Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection

Xu, X., Liu, C., Feng, Q., Yin, H., Song, L., & Song, D. (2017) · ACM SIGSAC Conference on Computer and Communications Security (CCS) · doi:10.1145/3133956.3134018 · Cited by 682 · see citing works

Deep learning for AI

Bengio, Y., LeCun, Y., & Hinton, G. E. (2021) · Communications of the ACM · doi:10.1145/3448250 · Cited by 676 · see citing works

Deep learning in video multi-object tracking: A survey

Ciaparrone, G., Luque Sánchez, F., Tabik, S., Troiano, L., Tagliaferri, R., & Herrera, F. (2020) · Neurocomputing · doi:10.1016/j.neucom.2019.11.023 · Cited by 665 · see citing works

L2-Net: Deep Learning of Discriminative Patch Descriptor in Euclidean Space

Tian, Y., Fan, B., & Wu, F. (2017) · 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.2017.649 · Cited by 601 · see citing works

Autoencoding beyond pixels using a learned similarity metricPreprint

Larsen, A., Sønderby, S. K., Larochelle, H., & Winther, O. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1512.09300 · Cited by 712 · see citing works

A review of object detection based on deep learning

Xiao, Y., Tian, Z., Yu, J., Zhang, Y., Liu, S., Du, S., & Lan, X. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-08976-6 · Cited by 584 · see citing works

Deep Learning via Semi-supervised Embedding

Weston, J., Ratle, F., Mobahi, H., & Collobert, R. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-35289-8_34 · Cited by 577 · see citing works

Deep Metric Learning with Angular Loss

Wang, J., Zhou, F., Wen, S., Liu, X., & Lin, Y. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.283 · Cited by 563 · see citing works

A Siamese Long Short-Term Memory Architecture for Human Re-identification

Varior, R. R., Shuai, B., Lu, J., Xu, D., & Wang, G. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46478-7_9 · Cited by 553 · see citing works

Unsupervised Deep Change Vector Analysis for Multiple-Change Detection in VHR Images

Saha, S., Bovolo, F., & Bruzzone, L. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2018.2886643 · Cited by 524 · see citing works

Geodesic Convolutional Neural Networks on Riemannian Manifolds

Masci, J., Boscaini, D., Bronstein, M. M., & Vandergheynst, P. (2015) · 2015 IEEE International Conference on Computer Vision Workshop (ICCVW) · doi:10.1109/iccvw.2015.112 · Cited by 721 · see citing works

Learning to Model the Tail

Wang, Y.-X., Ramanan, D., & Hebert, M. (2017) · neural information processing systems · Cited by 468 · see citing works

Multi-Attention Multi-Class Constraint for Fine-grained Image Recognition

Sun, M., Yuan, Y., Zhou, F., & Ding, E. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01270-0_49 · Cited by 441 · see citing works

AUTOMATIC SIGNATURE VERIFICATION: THE STATE OF THE ART—1989–1993

Leclerc, F., & Réjean Plamondon, B. (1994) · International Journal of Pattern Recognition and Artificial Intelligence · doi:10.1142/s0218001494000346 · Cited by 437 · see citing works

Proxy Anchor Loss for Deep Metric Learning

Kim, S., Kim, D.-W., Cho, M., & Kwak, S. (2020) · 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/cvpr42600.2020.00330 · Cited by 437 · see citing works

Extractive Summarization as Text Matching

Zhong, M., Liu, P., Chen, Y., Wang, D., Qiu, X., & Huang, X. (2020) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2020.acl-main.552 · Cited by 450 · see citing works

Medical image classification using synergic deep learning

Zhang, J., Xie, Y., Wu, Q., & Xia, Y. (2019) · Medical Image Analysis · doi:10.1016/j.media.2019.02.010 · Cited by 398 · see citing works

3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration

Yew, Z. J., & Lee, G. H. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01267-0_37 · Cited by 393 · see citing works

Semantic Instance Segmentation with a Discriminative Loss FunctionPreprint

Brabandere, B. D., Neven, D., & Gool, L. V. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1708.02551 · Cited by 404 · see citing works

Multi-Perspective Sentence Similarity Modeling with Convolutional Neural Networks

He, H., Gimpel, K., & Lin, J. (2015) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d15-1181 · Cited by 378 · see citing works

A survey: Deep learning for hyperspectral image classification with few labeled samples

Jia, S., Jiang, S., Lin, Z., Li, N., Xu, M., & Yu, S. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.03.035 · Cited by 388 · see citing works

Predicting protein–protein interactions through sequence-based deep learning

Hashemifar, S. S., Neyshabur, B., Khan, A. A., & Xu, J. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty573 · Cited by 370 · see citing works

Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking

Yu, J., Yang, X., Gao, F., & Tao, D. (2016) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2016.2591583 · Cited by 364 · see citing works

Learning Text Similarity with Siamese Recurrent Networks

Neculoiu, P., Versteegh, M., & Rotaru, M. (2016) · Proceedings of the 1st Workshop on Representation Learning for NLP · doi:10.18653/v1/w16-1617 · Cited by 341 · see citing works

Semantic Drift Compensation for Class-Incremental Learning

Yu, L., Twardowski, B., Liu, X., Herranz, L., Wang, K., Cheng, Y., Jui, S., & van de Weijer, J. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00701 · Cited by 340 · see citing works

Natural Language Inference by Tree-Based Convolution and Heuristic Matching

Mou, L.-L., Men, R., Li, G., Xu, Y., Zhang, L., Yan, R., & Jin, Z. (2015) · Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/p16-2022 · Cited by 376 · see citing works

Deep learning from temporal coherence in video

Mobahi, H., Collobert, R., & Weston, J. (2009) · Proceedings of the 26th Annual International Conference on Machine Learning · doi:10.1145/1553374.1553469 · Cited by 328 · see citing works

Domain Adaptation for Visual Applications: A Comprehensive SurveyPreprint

Csurka, G. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1702.05374 · Cited by 324 · see citing works

A Visualized Botnet Detection System Based Deep Learning for the Internet of Things Networks of Smart Cities

Vinayakumar, R., Alazab, M., Srinivasan, S., Pham, Q., Soman, K. P., & Simran, K. (2020) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2020.2971952 · Cited by 323 · see citing works

Backbone is All Your Need: A Simplified Architecture for Visual Object Tracking

Chen, B., Li, P., Bai, L., Qiao, L., Shen, Q., Li, B., Gan, W., Wu, W., & Ouyang, W. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20047-2_22 · Cited by 328 · see citing works

Comparative Evaluation of Hand-Crafted and Learned Local Features

Schönberger, J. L., Hans, H., Sattler, T., & Pollefeys, M. (2017) · 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.2017.736 · Cited by 313 · see citing works

Learning feed-forward one-shot learnersPreprint

Bertinetto, L., Henriques, J. F., Valmadre, J., Torr, P. H. S., & Vedaldi, A. (2016) · Oxford University Research Archive (ORA) (University of Oxford) · doi:10.48550/arxiv.1606.05233 · Cited by 393 · see citing works

Seeing Motion in the Dark

Chen, C., Chen, Q., Do, M. N., & Koltun, V. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00328 · Cited by 310 · see citing works

Neural Ranking Models with Weak Supervision

Dehghani, M., Zamani, H., Severyn, A., Kamps, J., & Croft, W. B. (2017) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3077136.3080832 · Cited by 306 · see citing works

Adversarially Occluded Samples for Person Re-identification

Huang, H., Li, D., Zhang, Z., Chen, X., & Huang, K. (2018) · 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.2018.00535 · Cited by 304 · see citing works

From Facial Expression Recognition to Interpersonal Relation Prediction

Zhang, Z., Luo, P., Loy, C. C., & Tang, X. (2017) · International Journal of Computer Vision · doi:10.1007/s11263-017-1055-1 · Cited by 304 · see citing works

Universal Correspondence NetworkPreprint

Choy, C., Gwak, J., Savarese, S., & Chandraker, M. K. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1606.03558 · Cited by 300 · see citing works

Deep Metric Learning via Facility Location

Song, H. O., Jegelka, S., Rathod, V., & Murphy, K. P. (2017) · 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.2017.237 · Cited by 293 · see citing works

SemEval-2018 Task 3: Irony Detection in English Tweets

Hee, C. V., Lefever, E., & Hoste, V. (2018) · International Workshop on Semantic Evaluation (SemEval) · doi:10.18653/v1/s18-1005 · Cited by 299 · see citing works

Smooth Neighbors on Teacher Graphs for Semi-Supervised Learning

Luo, Y., Zhu, J., Li, M., Ren, Y., & Zhang, B. (2018) · 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.2018.00927 · Cited by 271 · see citing works

How Transferable are Neural Networks in NLP Applications?

Mou, L., Zhao, M., Yan, R., Li, G., Xu, Y., Zhang, L., & Jin, Z. G. (2016) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d16-1046 · Cited by 310 · see citing works

Robust Point Cloud Registration Framework Based on Deep Graph Matching

Fu, K., Liu, S., Luo, X., & Wang, M. (2021) · 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/cvpr46437.2021.00878 · Cited by 281 · see citing works

Transfer Learning

Yang, Q., Zhang, Y., Dai, W., & Pan, S. J. (2020) · Cambridge University Press eBooks · doi:10.1017/9781139061773 · Cited by 272 · see citing works

Supervised Deep Feature Extraction for Hyperspectral Image Classification

Liu, B., Yu, X., Zhang, P., Yu, A., Fu, Q., & Wei, X. (2017) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2017.2769673 · Cited by 265 · see citing works

Neural Natural Language Inference Models Enhanced with External Knowledge

Chen, Q., Zhu, X., Ling, Z.-H., Inkpen, D. Z., & Wei, S. (2018) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/p18-1224 · Cited by 258 · see citing works

MinkLoc3D: Point Cloud Based Large-Scale Place Recognition

Komorowski, J. (2021) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv48630.2021.00183 · Cited by 258 · see citing works

Interpretable Drug Target Prediction Using Deep Neural Representation

Gao, K. Y., Fokoue, A., Luo, H., Iyengar, A., Dey, S., & Zhang, P. (2018) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2018/468 · Cited by 248 · see citing works

CrossTransformers: spatially-aware few-shot transferPreprint

Doersch, C., Gupta, A., & Zisserman, A. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.11498 · Cited by 255 · see citing works

Siamese Network for RGB-D Salient Object Detection and Beyond

Fu, K., Fan, D.-P., Ji, G.-P., Zhao, Q., Shen, J., & Zhu, C. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3073689 · Cited by 243 · see citing works

SAFE: Self-Attentive Function Embeddings for Binary Similarity

Massarelli, L., Luna, G. A. D., Petroni, F., Baldoni, R., & Querzoni, L. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-22038-9_15 · Cited by 243 · see citing works

Research Progress on Few-Shot Learning for Remote Sensing Image Interpretation

Sun, X., Wang, B., Wang, Z., Li, H., Li, H.-C., & Fu, K. (2021) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2021.3052869 · Cited by 243 · see citing works

Past, present and future approaches using computer vision for animal re‐identification from camera trap data

Schneider, S., Taylor, G. W., Linquist, S., & Kremer, S. C. (2019) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13133 · Cited by 245 · see citing works

Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement

He, H., & Lin, J. (2016) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/n16-1108 · Cited by 240 · see citing works

De novo design of protein interactions with learned surface fingerprints

Gaínza, P., Wehrle, S., Hall‐Beauvais, A. V., Marchand, A., Scheck, A., Harteveld, Z., Buckley, S., Ni, D., Tan, S., Sverrisson, F., et al. (2023) · Nature · doi:10.1038/s41586-023-05993-x · Cited by 241 · see citing works

Learning Type-Aware Embeddings for Fashion Compatibility

Vasileva, M. I., Plummer, B. A., Dusad, K., Rajpal, S., Kumar, R., & Forsyth, D. A. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01270-0_24 · Cited by 235 · see citing works

Learning Combinatorial Embedding Networks for Deep Graph Matching

Wang, R., Yan, J., & Yang, X. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00315 · Cited by 239 · see citing works

A Survey of Single-Scene Video Anomaly Detection

Ramachandra, B., Jones, M., & Vatsavai, R. R. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.3040591 · Cited by 244 · see citing works

Actions ~ Transformations

Wang, X., Farhadi, A., & Gupta, A. (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.2016.291 · Cited by 228 · see citing works

Video-based surgical skill assessment using 3D convolutional neural networks

Funke, I., Mees, S. T., Weitz, J., & Speidel, S. (2019) · International Journal of Computer Assisted Radiology and Surgery · doi:10.1007/s11548-019-01995-1 · Cited by 227 · see citing works

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