Gradient Flow in Recurrent Nets: The Difficulty of Learning LongTerm Dependencies

Deep learning in neural networks: an overview

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LSTM: A Search Space Odyssey

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Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network

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OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields

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Transformer-XL: Attentive language models beyond a fixed-length context

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Supervised Sequence Labelling with Recurrent Neural Networks

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Convolutional Pose Machines

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Barren plateaus in quantum neural network training landscapes

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Deep Hashing Network for Unsupervised Domain Adaptation

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A Survey of the Usages of Deep Learning for Natural Language Processing

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Deep neural networks: a new framework for modeling biological vision and brain information processing

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DeepTox: toxicity prediction using deep learning

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Multi-column deep neural network for traffic sign classification

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Bidirectional LSTM Networks for Improved Phoneme Classification and Recognition

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Rotation-invariant convolutional neural networks for galaxy morphology prediction

Dieleman, S., Willett, K. W., & Dambre, J. (2015) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stv632 · Cited by 781

View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data

Zhang, P., Lan, C., Xing, J., Zeng, W., Xue, J., & Zheng, N. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.233 · Cited by 691

A novel time–frequency Transformer based on self–attention mechanism and its application in fault diagnosis of rolling bearings

Ding, Y., Jia, M., Miao, Q., & Cao, Y. (2022) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2021.108616 · Cited by 559

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

Rives, A., Meier, J., Sercu, T., Goyal, S., Lin, Z., Liu, J., Guo, D., Ott, M., Zitnick, C. L., Ma, J., et al. (2019) · doi:10.1101/622803 · Cited by 3,280

Unsupervised Pre-training of a Deep LSTM-based Stacked Autoencoder for Multivariate Time Series Forecasting Problems

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Bidirectional RNN for Medical Event Detection in Electronic Health Records

Jagannatha, A. N., & Yu, H. (2016) · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · doi:10.18653/v1/n16-1056 · Cited by 314

Multi-dimensional Recurrent Neural Networks

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Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification

Rodriguez, P., Cucurull, G., Gonzalez, J., Gonfaus, J. M., Nasrollahi, K., Moeslund, T. B., & Roca, F. X. (2022) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2017.2662199 · Cited by 297

LSTM-Modeling of continuous emotions in an audiovisual affect recognition framework

Wöllmer, M., Kaiser, M., Eyben, F., Schuller, B., & Rigoll, G. (2013) · Image and Vision Computing · doi:10.1016/j.imavis.2012.03.001 · Cited by 288

3D Human Action Representation Learning via Cross-View Consistency Pursuit

Li, L., Wang, M., Ni, B., Wang, H., Yang, J., & Zhang, W. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.00471 · Cited by 236

Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 2: a discussion of chemical and biological data

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Prediction of asynchronous dimensional emotion ratings from audiovisual and physiological data

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Cyber threat detection based on artificial neural networks using event profiles

Lee, J., Kim, J., Kim, I., & Han, K. (2019) · IEEE Access · doi:10.1109/access.2019.2953095 · Cited by 188

MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning

Lei, J., Wang, L., Shen, Y., Yu, D., Berg, T., & Bansal, M. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2020.acl-main.233 · Cited by 179

Ultrasound Standard Plane Detection Using a Composite Neural Network Framework

Chen, H., Wu, L., Dou, Q., Qin, J., Li, S., Cheng, J.-Z., Ni, D., & Heng, P.-A. (2017) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2017.2685080 · Cited by 164

A survey on aspect-based sentiment classification

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Deep Learning for Mobile Multimedia: A Survey

Ota, K., Dao, M. S., Mezaris, V., & Natale, F. G. B. D. (2017) · ACM Transactions on Multimedia Computing, Communications, and Applications · doi:10.1145/3092831 · Cited by 135

Knowledge Graph Representation with Jointly Structural and Textual Encoding

Xu, J., Qiu, X., Chen, K., & Huang, X. (2017) · Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2017/183 · Cited by 121

Locally Confined Modality Fusion Network With a Global Perspective for Multimodal Human Affective Computing

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LearningQ: A Large-Scale Dataset for Educational Question Generation

Chen, G., Yang, J., Hauff, C., & Houben, G.-J. (2018) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v12i1.14987 · Cited by 83

BERT-based ensemble learning for multi-aspect hate speech detection

Mazari, A. C., Boudoukhani, N., & Djeffal, A. (2024) · Cluster Computing · doi:10.1007/s10586-022-03956-x · Cited by 89

Real-time Arm Skeleton Tracking and Gesture Inference Tolerant to Missing Wearable Sensors

Liu, Y., Li, Z., Liu, Z., & Wu, K. (2019) · Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services · doi:10.1145/3307334.3326109 · Cited by 71

Multi-Modality Multi-Task Recurrent Neural Network for Online Action Detection

Liu, J., Li, Y., Song, S., Xing, J., Lan, C., & Zeng, W. (2019) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2018.2799968 · Cited by 62

Anomaly Detection for Cyber-Security Based on Convolution Neural Network : A survey

Alabadi, M., & Celik, Y. (2020) · 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA) · doi:10.1109/hora49412.2020.9152899 · Cited by 55

A Multi-scale Approach to Gesture Detection and Recognition

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Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation

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Semi-supervised facial expression recognition using reduced spatial features and Deep Belief Networks

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Deep Big Multilayer Perceptrons for Digit Recognition

Cireşan, D. C., Meier, U., Gambardella, L. M., & Schmidhuber, J. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-35289-8_31 · Cited by 48

Abstractive summarization of long texts by representing multiple compositionalities with temporal hierarchical pointer generator network

Moirangthem, D. S., & Lee, M. (2020) · Neural Networks · doi:10.1016/j.neunet.2019.12.022 · Cited by 30

Application of Ai Techniques in Monitoring and Operation of Power Systems

Gao, D. W., Wang, Q., Zhang, F., Yang, X., Huang, Z., Ma, S., Li, Q., Gong, X., & Wang, F.-Y. (2019) · Frontiers in Energy · doi:10.1007/s11708-018-0589-4 · Cited by 28

Cross-dataset deep transfer learning for activity recognition

Gjoreski, M., Kalabakov, S., Luštrek, M., Gams, M., & Gjoreski, H. (2019) · Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers · doi:10.1145/3341162.3344865 · Cited by 28

Deep Learning Bidirectional LSTM based Detection of Prolongation and Repetition in Stuttered Speech using Weighted MFCC

Gupta, S., S., R., K., R., & Verma, R. (2020) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2020.0110941 · Cited by 26

Asynchronous and Event-Based Fusion Systems for Affect Recognition on Naturalistic Data in Comparison to Conventional Approaches

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A Multi-task Approach to Learning Multilingual Representations

Singla, K., Can, D., & Narayanan, S. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) · doi:10.18653/v1/p18-2035 · Cited by 22

Token turing machines

Ryoo, M. S., Gopalakrishnan, K., Kahatapitiya, K., Xiao, T., Rao, K., Stone, A., Lu, Y., Ibarz, J., & Arnab, A. (2022) · arXiv · doi:10.48550/arxiv.2211.09119 · Cited by 21

Tandem decoding of children's speech for keyword detection in a child-robot interaction scenario

Wöllmer, M., Schuller, B., Batliner, A., Steidl, S., & Seppi, D. (2011) · ACM Transactions on Speech and Language Processing · doi:10.1145/1998384.1998386 · Cited by 18

A deep fusion model for human $vs$. Machine-generated essay classification

Corizzo, R., & Leal-Arenas, S. (2023) · 2023 International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn54540.2023.10191322 · Cited by 13

Autoencoding sensory substitution

Tóth, V., & Parkkonen, L. (2019) · Unpublished · doi:10.13140/rg.2.2.10576.87048 · Cited by 7