Original approach for the localisation of objects in images

Gradient-based learning applied to document recognition

Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998) · Proceedings of the IEEE · doi:10.1109/5.726791 · Cited by 58,805 · see citing works

Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.81 · Cited by 32,684 · see citing works

Feature Pyramid Networks for Object Detection

Lin, T.-Y., Dollar, P., Girshick, R., He, K., Hariharan, B., & Belongie, S. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.106 · Cited by 30,939 · see citing works

Focal Loss for Dense Object Detection

Lin, T.-Y., Goyal, P., Girshick, R., He, K., & Dollar, P. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.324 · Cited by 30,581 · 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

Focal Loss for Dense Object Detection

Lin, T.-Y., Goyal, P., Girshick, R., He, K., & Dollar, P. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2858826 · Cited by 9,556 · see citing works

A ConvNet for the 2020s

Liu, Z., Mao, H., Wu, C.-Y., Feichtenhofer, C., Darrell, T., & Xie, S. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.01167 · Cited by 8,494 · see citing works

Recent advances in convolutional neural networks

Gu, J., Wang, Z., Kuen, J., Ma, L., Shahroudy, A., Shuai, B., Liu, T., Wang, X., Wang, G., Cai, J., et al. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2017.10.013 · Cited by 6,576 · see citing works

Object Detection in 20 Years: A Survey

Zou, Z., Chen, K., Shi, Z., Guo, Y., & Ye, J. (2023) · Proceedings of the IEEE · doi:10.1109/jproc.2023.3238524 · Cited by 3,689 · see citing works

Neural network-based face detection

Rowley, H. A., Baluja, S., & Kanade, T. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.655647 · Cited by 3,554 · see citing works

Detecting faces in images: a survey

Yang, M.-H., Kriegman, D. J., & Ahuja, N. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.982883 · Cited by 3,430 · see citing works

Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks

Oquab, M., Bottou, L., Laptev, I., & Sivic, J. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.222 · Cited by 3,150 · see citing works

Deep Learning for Generic Object Detection: A Survey

Liu, L., Ouyang, W., Wang, X., Fieguth, P., Chen, J., Liu, X., & Pietikäinen, M. (2020) · International Journal of Computer Vision · doi:10.1007/s11263-019-01247-4 · Cited by 2,965 · see citing works

Region-based convolutional networks for accurate object detection and segmentation

Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2437384 · Cited by 2,912 · see citing works

Learning Hierarchical Features for Scene Labeling

Farabet, C., Couprie, C., Najman, L., & LeCun, Y. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.231 · Cited by 2,620 · see citing works

Training support vector machines: an application to face detection

Osuna, E., Freund, R. M., & Girosi, F. (2002) · 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.1997.609310 · Cited by 2,481 · see citing works

Convolutional networks and applications in vision

LeCun, Y., Kavukcuoglu, K., & Farabet, C. (2010) · Proceedings of 2010 IEEE International Symposium on Circuits and Systems · doi:10.1109/iscas.2010.5537907 · Cited by 2,213 · see citing works

Panoptic Segmentation

Kirillov, A., He, K., Girshick, R., Rother, C., & Dollár, P. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00963 · Cited by 1,659 · see citing works

A general framework for object detection

Papageorgiou, C., Oren, M., & Poggio, T. (2002) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.1998.710772 · Cited by 1,437 · see citing works

A convolutional neural network cascade for face detection

Li, H., Lin, Z., Shen, X., Brandt, J., & Hua, G. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7299170 · Cited by 1,390 · see citing works

Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks

Bell, S., Zitnick, C. L., Bala, K., & Girshick, R. (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.2016.314 · Cited by 1,344 · see citing works

Learning methods for generic object recognition with invariance to pose and lighting

LeCun, Y., Huang, F. J., & Bottou, L. (2004) · Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004. · doi:10.1109/cvpr.2004.1315150 · Cited by 1,324 · see citing works

A Trainable System for Object Detection

Papageorgiou, C., & Poggio, T. (2000) · International Journal of Computer Vision · doi:10.1023/a:1008162616689 · Cited by 1,289 · see citing works

GradientBased Learning Applied to Document Recognition

Haykin, S., & Kosko, B. (2009) · Institute of Electrical and Electronics Engineers eBooks · doi:10.1109/9780470544976.ch9 · Cited by 1,208 · see citing works

Example-based object detection in images by components

Mohan, A., Papageorgiou, C., & Poggio, T. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.917571 · Cited by 954 · see citing works

Object Recognition with Gradient-Based Learning

LeCun, Y., Haffner, P., Bottou, L., & Bengio, Y. (1999) · Lecture Notes in Computer Science · doi:10.1007/3-540-46805-6_19 · Cited by 947 · see citing works

Face Detection with the Faster R-CNN

Jiang, H., & Miller, E. G. (2017) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2017.82 · Cited by 823 · see citing works

Pedestrian Detection with Unsupervised Multi-stage Feature Learning

Sermanet, P., Kavukcuoglu, K., Chintala, S., & LeCun, Y. (2013) · 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.2013.465 · Cited by 753 · see citing works

Pedestrian detection using wavelet templates

Oren, M., Papageorgiou, C., Sinha, P., Osuna, E., & Poggio, T. (2002) · 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.1997.609319 · Cited by 694 · see citing works

Multi-view Face Detection Using Deep Convolutional Neural Networks

Farfade, S., Saberian, M. J., & Li, L.-J. (2015) · International Conference on Multimedia Retrieval · doi:10.1145/2671188.2749408 · Cited by 591 · see citing works

From Facial Parts Responses to Face Detection: A Deep Learning Approach

Yang, S., Luo, P., Loy, C. C., & Tang, X. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.419 · Cited by 574 · see citing works

Application of deep learning algorithms in geotechnical engineering: a short critical review

Zhang, W., Li, H., Li, Y., Liu, H., Chen, Y., & Ding, X. (2021) · Artificial Intelligence Review · doi:10.1007/s10462-021-09967-1 · Cited by 548 · see citing works

Convolutional face finder: a neural architecture for fast and robust face detection

García, C., & Delakis, M. (2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2004.97 · Cited by 545 · see citing works

Rotation Invariant Neural Network-Based Face Detection

Rowley, H. A., Baluja, S., & Takeo Kanade, A. (2005) · 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.1998.698721 · Cited by 471 · see citing works

Deformable part models are convolutional neural networks

Girshick, R., Iandola, F., Darrell, T., & Malik, J. (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.2015.7298641 · Cited by 423 · see citing works

TensorMask: A Foundation for Dense Object Segmentation

Chen, X., Girshick, R., He, K., & Dollár, P. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00215 · Cited by 414 · see citing works

DenseBox: Unifying Landmark Localization with End to End Object Detection

Huang, L., Yang, Y., Deng, Y., & Yu, Y. (2015) · arXiv · doi:10.48550/arxiv.1509.04874 · Cited by 407 · see citing works

Untitled work

(1995) · Cited by 359 · see citing works

CNN-based image analysis for malaria diagnosis

Liang, Z., Powell, A. J., Ersoy, I., Poostchi, M., Silamut, K., Palaniappan, K., Guo, P. W., Hossain, M. A., Sameer, A., Maude, R. J., et al. (2016) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2016.7822567 · Cited by 349 · see citing works

Evolution of Image Segmentation using Deep Convolutional Neural Network: A Survey

Sultana, F., Sufian, A., & Dutta, P. (2020) · Knowledge-Based Systems · doi:10.1016/j.knosys.2020.106062 · Cited by 346 · see citing works

Neural network-based face detection

Rowley, H. A., Baluja, S., & Takeo Kanade, A. (1996) · 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.1996.517075 · Cited by 332 · see citing works

Large-scale Learning with SVM and Convolutional for Generic Object Categorization

Huang, F. J., & LeCun, Y. (2006) · 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.2006.164 · Cited by 320 · see citing works

FaceBoxes: A CPU real-time face detector with high accuracy

Zhang, S., Zhu, X., Lei, Z., Shi, H., Wang, X., & Li, S. Z. (2017) · IEEE International Joint Conference on Biometrics (IJCB) · doi:10.1109/btas.2017.8272675 · Cited by 316 · see citing works

Mapping from Frame-Driven to Frame-Free Event-Driven Vision Systems by Low-Rate Rate Coding and Coincidence Processing--Application to Feedforward ConvNets

Pérez‐Carrasco, J. A., Zhao, B., Serrano, C., Acha, B., Serrano‐Gotarredona, T., Chen, S., & Linares-Barranco, B. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.71 · Cited by 315 · see citing works

A fast and accurate face detector based on neural networks

Feraund, R., Bernier, O., Viallet, J. E., & Collobert, M. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.899945 · Cited by 288 · see citing works

Toward automatic phenotyping of developing embryos from videos

Ning, F., Delhomme, D., LeCun, Y., Piano, F., Bottou, L., & Barbano, P. E. (2005) · IEEE Transactions on Image Processing · doi:10.1109/tip.2005.852470 · Cited by 260 · see citing works

Face detection from color images using a fuzzy pattern matching method

Wu, H., Chen, Q., & Yachida, M. (1999) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.771326 · Cited by 245 · see citing works

Deep Learning for Generic Object Detection: A Survey

Liu, L., Ouyang, W., Wang, X., Fieguth, P., Chen, J., Liu, X., & Pietikäinen, M. (2018) · arXiv · doi:10.48550/arxiv.1809.02165 · Cited by 2,965 · see citing works

A Taxonomy of Deep Convolutional Neural Nets for Computer Vision

Srinivas, S., Sarvadevabhatla, R. K., Mopuri, K. R., Prabhu, N., Kruthiventi, S. S. S., & Babu, R. V. (2016) · Frontiers in Robotics and AI · doi:10.3389/frobt.2015.00036 · Cited by 229 · see citing works

Joint Training of Cascaded CNN for Face Detection

Qin, H., Yan, J., Li, X., & Hu, X. (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.2016.376 · Cited by 217 · see citing works

Automated Lung Sound Classification Using a Hybrid CNN-LSTM Network and Focal Loss Function

Πετμεζάς, Γ., Cheimariotis, G., Stefanopoulos, L., Rocha, B., Paiva, R. P., Katsaggelos, A. K., & Maglaveras, N. (2022) · Sensors · doi:10.3390/s22031232 · Cited by 216 · see citing works

Synergistic Face Detection and Pose Estimation with Energy-Based Models

Osadchy, M., LeCun, Y., & Miller, M. L. (2006) · Lecture notes in computer science · doi:10.1007/11957959_10 · Cited by 211 · see citing works

Pedestrian detection with convolutional neural networks

Szarvas, M., Yoshizawa, A., Yamamoto, M., & Ogata, J. (2005) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2005.1505106 · Cited by 206 · see citing works

Dynamic prediction for attitude and position in shield tunneling: A deep learning method

Zhou, C., Hengcheng, X., Ding, L., Wei, L., & Zhou, Y. (2019) · Automation in Construction · doi:10.1016/j.autcon.2019.102840 · Cited by 199 · see citing works

Crack Detection and Segmentation Using Deep Learning with 3D Reality Mesh Model for Quantitative Assessment and Integrated Visualization

Kalfarisi, R., Wu, Z. Y., & Soh, K. (2020) · Journal of Computing in Civil Engineering · doi:10.1061/(asce)cp.1943-5487.0000890 · Cited by 186 · see citing works

Car Detection from Low-Altitude UAV Imagery with the Faster R-CNN

Xu, Y., Yu, G., Wang, Y., Wu, X., & Ma, Y. (2017) · Journal of Advanced Transportation · doi:10.1155/2017/2823617 · Cited by 183 · see citing works

Investigations of Object Detection in Images/Videos Using Various Deep Learning Techniques and Embedded Platforms—A Comprehensive Review

Chintakindi, B. M., Hashmi, M. F., Bokde, N. D., & Geem, Z. W. (2020) · Applied Sciences · doi:10.3390/app10093280 · Cited by 178 · see citing works

Faceness-Net: Face Detection through Deep Facial Part Responses

Yang, S., Luo, P., Loy, C. C., & Tang, X. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2738644 · Cited by 169 · see citing works

Automatic fabric defect detection using a deep convolutional neural network

Jing, J., Ma, H., & Zhang, H. (2019) · Coloration Technology · doi:10.1111/cote.12394 · Cited by 164 · see citing works

Research on the deep learning of the small sample data based on transfer learning

Zhao, W. (2017) · AIP conference proceedings · doi:10.1063/1.4992835 · Cited by 149 · see citing works

Gene Selection and Classification of Microarray Data Using Convolutional Neural Network

Zeebaree, D. Q., Haron, H., & Abdulazeez, A. M. (2018) · International Conference on Advanced Science and Engineering (ICOASE) · doi:10.1109/icoase.2018.8548836 · Cited by 143 · see citing works

Actions and Attributes from Wholes and Parts

Gkioxari, G., Girshick, R., & Malik, J. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.284 · Cited by 142 · see citing works

Face Detection With Different Scales Based on Faster R-CNN

Wu, W., Yin, Y., Wang, X., & Xu, D. (2018) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2859482 · Cited by 135 · see citing works

Scale-Aware Face Detection

Hao, Z., Liu, Y., Qin, H., Yan, J., Li, X., & Hu, X. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.207 · Cited by 134 · see citing works

Recent Advances in Object Detection in the Age of Deep Convolutional Neural NetworksPreprint

Agarwal, S., du Terrail, J. O., & Jurie, F. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1809.03193 · Cited by 133 · see citing works

Context-Aware CNNs for Person Head Detection

Vu, T.-H., Osokin, A., & Laptev, I. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.331 · Cited by 129 · see citing works

Face Detection and Segmentation Based on Improved Mask R-CNN

Lin, K., Zhao, H., Lv, J., Li, C., Liu, X., Chen, R., & Zhao, R. (2020) · Discrete Dynamics in Nature and Society · doi:10.1155/2020/9242917 · Cited by 129 · see citing works

Large-Scale FPGA-Based Convolutional Networks

Farabet, C., LeCun, Y., Kavukcuoglu, K., Martini, B., Akselrod, P., Talay, S., & Culurciello, E. (2011) · Cambridge University Press eBooks · doi:10.1017/cbo9781139042918.020 · Cited by 121 · see citing works

State-of-the-Art Deep Learning Methods on Electrocardiogram Data: Systematic Review

Πετμεζάς, Γ., Stefanopoulos, L., Kilintzis, V., Tzavelis, A., Rogers, J. A., Katsaggelos, A. K., & Maglaveras, N. (2022) · JMIR Medical Informatics · doi:10.2196/38454 · Cited by 120 · see citing works

Categorization by Learning and Combining Object Parts

Heisele, B., Serre, T., Pontil, M., Vetter, T. R., & Poggio, T. (2001) · Cited by 118 · see citing works

An Event-Driven Multi-Kernel Convolution Processor Module for Event-Driven Vision Sensors

Camuñas-Mesa, L. A., Zamarreño-Ramos, C., Linares-Barranco, A., Acosta, A. J., Serrano‐Gotarredona, T., & Linares-Barranco, B. (2011) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2011.2167409 · Cited by 115 · see citing works

A Deep Learning Approach for Face Detection using YOLO

Garg, D., Goel, P., Pandya, S., Ganatra, A. P., & Kotecha, K. V. (2018) · IEEE Pune Section International Conference (PuneCon) · doi:10.1109/punecon.2018.8745376 · Cited by 113 · see citing works

Multi-modal system for locating heads and faces

Graf, H. P., Cosatto, E., Gibbon, D. C., Kocheisen, M., & Petajan, E. D. (2002) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.1996.557248 · Cited by 113 · see citing works

A Novel Stacked CNN for Malarial Parasite Detection in Thin Blood Smear Images

Umer, M., Sadiq, S., Ahmad, M. I., Ullah, S., Choi, G. S., & Mehmood, A. (2020) · IEEE Access · doi:10.1109/access.2020.2994810 · Cited by 110 · see citing works

Multicasting Mesh AER: A Scalable Assembly Approach for Reconfigurable Neuromorphic Structured AER Systems. Application to ConvNets

Zamarreño-Ramos, C., Linares-Barranco, A., Serrano‐Gotarredona, T., & Linares-Barranco, B. (2012) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2012.2195725 · Cited by 103 · see citing works

The Understanding of Deep Learning: A Comprehensive Review

Mishra, R. K., Reddy, G. Y. S., & Pathak, H. (2021) · Mathematical Problems in Engineering · doi:10.1155/2021/5548884 · Cited by 99 · see citing works

A review of image-based automatic facial landmark identification techniques

Johnston, B., & de Chazal, P. (2018) · EURASIP Journal on Image and Video Processing · doi:10.1186/s13640-018-0324-4 · Cited by 94 · see citing works

Global training of document processing systems using graph transformer networks

Bottou, L., Bengio, Y., & LeCun, Y. (2002) · 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.1997.609370 · Cited by 89 · see citing works

Design and analysis of machine learning exchange-correlation functionals via rotationally invariant convolutional descriptors

Lei, X. L., & Medford, A. J. (2019) · Physical Review Materials · doi:10.1103/physrevmaterials.3.063801 · Cited by 79 · see citing works

A New Benchmark on American Sign Language Recognition using Convolutional Neural Network

Rahman, M. M., Islam, M. S., Rahman, M. H., Sassi, R., Rivolta, M. W., & Aktaruzzaman, M. (2019) · International Conference on Sustainable Technologies for Industry 5.0 (STI) · doi:10.1109/sti47673.2019.9067974 · Cited by 78 · see citing works

A hybrid model of CNN and LSTM autoencoder-based short-term PV power generation forecasting

Ibrahim, M. S., Gharghory, S. M., & Kamal, H. A. (2024) · Electrical Engineering · doi:10.1007/s00202-023-02220-8 · Cited by 78 · see citing works

A multi-scale cascade fully convolutional network face detector

Yang, Z., & Nevatia, R. (2016) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2016.7899705 · Cited by 77 · see citing works

Grid Loss: Detecting Occluded Faces

Opitz, M., Waltner, G., Poier, G., Possegger, H., & Bischof, H. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46487-9_24 · Cited by 75 · see citing works

Dual-source gramian angular field method and its application on fault diagnosis of drilling pump fluid end

Li, G., Ao, J., Hu, J., Hu, D., Liu, Y., & Huang, Z. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.121521 · Cited by 73 · see citing works

Detecting People in Artwork with CNNs

Westlake, N., Cai, H., & Hall, P. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46604-0_57 · Cited by 72 · see citing works

Face Detection Using GPU-Based Convolutional Neural Networks

Nasse, F., Thurau, C., & Fink, G. A. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-03767-2_10 · Cited by 68 · see citing works

Video deepfake detection using a hybrid CNN-LSTM-Transformer model for identity verification

Πετμεζάς, Γ., Vanian, V., Konstantoudakis, K., Almaloglou, E. E. I., & Zarpalas, D. (2025) · Multimedia Tools and Applications · doi:10.1007/s11042-024-20548-6 · Cited by 67 · see citing works

The future of bone regeneration: integrating AI into tissue engineering

MacKay, B., Marshall, K. M., Grant‐Jacob, J. A., Kanczler, J. M., Eason, R. W., Oreffo, R. O. C., & Mills, B. (2021) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/ac154f · Cited by 66 · see citing works

Fast and Accurate, Convolutional Neural Network Based Approach for Object Detection from UAV

Wang, X., Cheng, P., Liu, X., & Uzochukwu, B. M. (2018) · Annual Conference of the IEEE Industrial Electronics Society (IECON) · doi:10.1109/iecon.2018.8592805 · Cited by 64 · see citing works

Recognition Bangla Sign Language using Convolutional Neural Network

Islalm, M. S., Rahman, M. M., Rahman, M. H., Arifuzzaman, M., Sassi, R., & Aktaruzzaman, M. (2019) · International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) · doi:10.1109/3ict.2019.8910301 · Cited by 62 · see citing works

Mitochondria segmentation in electron microscopy volumes using deep convolutional neural network

Öztel, İ., Yolcu, G., Ersoy, I., White, T., & Bunyak, F. (2017) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2017.8217827 · Cited by 57 · see citing works

A 32$\,\times\,$32 Pixel Convolution Processor Chip for Address Event Vision Sensors With 155 ns Event Latency and 20 Meps Throughput

Camuñas-Mesa, L. A., Acosta, A. J., Zamarreño-Ramos, C., Serrano‐Gotarredona, T., & Linares-Barranco, B. (2010) · IEEE Transactions on Circuits and Systems I Regular Papers · doi:10.1109/tcsi.2010.2078851 · Cited by 55 · see citing works

Super-Resolution Simulation for Real-Time Prediction of Urban Micrometeorology

Onishi, R., Sugiyama, D., & Matsuda, K. (2019) · SOLA · doi:10.2151/sola.2019-032 · Cited by 53 · see citing works

Image representations and feature selection for multimedia database search

Evgeniou, T., Pontil, M., Papageorgiou, C., & Poggio, T. (2003) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2003.1209008 · Cited by 50 · see citing works

Low-Complexity Approximate Convolutional Neural Networks

Cintra, R. J., Duffner, S., García, C., & Leite, A. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2815435 · Cited by 50 · see citing works

An Effective Convolutional Neural Network for Classifying Red Blood Cells in Malaria Diseases

Quan, Q., Wang, J., & Liu, L. (2020) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-020-00367-7 · Cited by 49 · see citing works

On the applications of multimedia processing to communications

Cox, R. V., Haskell, B. G., LeCun, Y., Shahraray, B., & Rabiner, L. R. (1998) · Proceedings of the IEEE · doi:10.1109/5.664272 · Cited by 49 · see citing works

Convolutional neural network analysis of radiography images for rapid water quantification in PEM fuel cell

Pang, Y., Hao, L., & Wang, Y. (2022) · Applied Energy · doi:10.1016/j.apenergy.2022.119352 · Cited by 48 · see citing works

Small Aircraft Detection in Remote Sensing Images Based on YOLOv3

Zhao, K., & Ren, X. (2019) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/533/1/012056 · Cited by 42 · see citing works

Advances in Component-Based Face Detection

Bileschi, S., & Heisele, B. (2002) · Lecture notes in computer science · doi:10.1007/3-540-45665-1_11 · Cited by 42 · see citing works

Face Finding in Images

Vincent, J. M. (1995) · Springer eBooks · doi:10.1007/978-1-4757-2379-3_2 · Cited by 3 · see citing works

Neural Network Cascade for Facial Feature Localization

Sénéchal, T., Prévost, L., & Hanif, M. S. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-12159-3_13 · Cited by 6 · see citing works

Neural Network Based Face Localization

Hendrych, P. (2008) · Brno University of Technology Digital Library (Brno University of Technology)

Local binary patterns and neural network based technique for robust face detection and localization

Ņikišins, O., & Greitāns, M. (2012) · International Conference on Biometrics · Cited by 8 · see citing works

Automatic location of visual features by a system of multilayered perceptrons

Vincent, J. M., Waite, J. B., & Myers, D. J. (1992) · IEE Proceedings F Radar and Signal Processing · doi:10.1049/ip-f-2.1992.0058 · Cited by 18 · see citing works