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Gradient-based learning applied to document recognition

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Bidirectional recurrent neural networks

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Framewise phoneme classification with bidirectional LSTM and other neural network architectures

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Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks

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Best practices for convolutional neural networks applied to visual document analysis

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

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Bidirectional LSTM Networks for Improved Phoneme Classification and Recognition

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Backpropagation: Theory, architectures, and applications

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Data Augmentation for Offline Handwritten Text Recognition: A Systematic Literature Review

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Multi-source Multi-level Attention Networks for Visual Question Answering

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Investigating topological order using recurrent neural networks

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Perspective-Adaptive Convolutions for Scene Parsing

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Unmanned Aerial Vehicles (UAV) Networking Algorithms: Communication, Control, and AI-Based Approaches

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Face Mask Extraction in Video Sequence

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Comparison of Deep Learning Techniques in Detection of Sickle Cell Disease

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Inner and Outer Recursive Neural Networks for Chemoinformatics Applications

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Seeking Common but Distinguishing Difference, A Joint Aspect-based Sentiment Analysis Model

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Neural Networks for Handwriting Recognition

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A Fine-Grained Network for Joint Multimodal Entity-Relation Extraction

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Incorporating part-whole hierarchies into fully convolutional network for scene parsing

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Rethinking the Form of Latent States in Image Captioning

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Efficient Hardware Architectures for 1D- and MD-LSTM Networks

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Image Pre-Processing

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Toward an intelligent aluminum laser welded blanks (ALWBs) factory based on industry 4.0; a critical review and novel smart model

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Texture Classification Using 2D LSTM Networks

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Feature Learning and Deep Learning Architecture Survey

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Indirect Encoding of Neural Networks for Scalable Go

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Learning to Recognize Touch Gestures: Recurrent vs. Convolutional Features and Dynamic Sampling

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Online time-series forecasting using spiking reservoir

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No Padding Please: Efficient Neural Handwriting Recognition

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Fine-Grained Similarity Measurement between Educational Videos and Exercises

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A Novel LSTM-RNN Decoding Algorithm in CAPTCHA Recognition

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PREDICTION OF AIRCRAFT BOARDING TIME USING LSTM NETWORK

Schultz, M., & Reitmann, S. (2018) · Winter Simulation Conference · doi:10.1109/wsc.2018.8632532 · Cited by 20

Enhancing handwritten text recognition accuracy with gated mechanisms

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Knowledge Transfer Using Neural Network Based Approach for Handwritten Text Recognition

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DDoS detection in electric vehicle charging stations: A deep learning perspective via CICEV2023 dataset

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Machine learning applications to computational plasma physics and reduced-order plasma modeling: a perspective

Faraji, F., & Reza, M. (2024) · Journal of Physics D Applied Physics · doi:10.1088/1361-6463/ada167 · Cited by 27

An Efficient Hybrid Model for Arabic Text Recognition

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On Fast Deep Nets for AGI Vision

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Cross-Lingual Dependency Parsing with Late Decoding for Truly Low-Resource Languages

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A Deep Learning Approach for Identifying User Communities Based on Geographical Preferences and Its Applications to Urban and Environmental Planning

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Improved cuckoo search with particle swarm optimization for classification of compressed images

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Predictive resilience assessment of road networks based on dynamic multi-granularity graph neural network

Zang, D., Ding, Y., Zhao, J., Tang, K., & Zhu, H. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.128207 · Cited by 20

Underground Diagnosis Based on GPR and Learning in the Model Space

Chen, A., Zhou, X., Fan, Y., & Chen, H. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3347739 · Cited by 18

Writer Identification in Noisy Handwritten Documents

Ni, K. S., Callier, P., & Hatch, B. (2017) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2017.136 · Cited by 17

Long short-term memory based convolutional recurrent neural networks for large vocabulary speech recognition

Li, X., & Wu, X. H. (2015) · Interspeech (USB) · doi:10.21437/interspeech.2015-648 · Cited by 21

Spatio-Temporal Prediction for the Monitoring-Blind Area of Industrial Atmosphere Based on the Fusion Network

Bai, Y., Wang, X., Sun, Q., Jin, X.-B., Wang, X., Su, T., & Kong, J. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16203788 · Cited by 16

Greedy Transition-Based Dependency Parsing with Stack LSTMs

Ballesteros, M., Dyer, C., Goldberg, Y., & Smith, N. A. (2017) · Computational Linguistics · doi:10.1162/coli_a_00285 · Cited by 17

Multi-dimensional Connectionist Classification: Reading Text in One Step

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HySPA: Hybrid Span Generation for Scalable Text-to-Graph Extraction

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Scene analysis by mid-level attribute learning using 2D LSTM networks and an application to web-image tagging

Byeon, W., Liwicki, M., & Breuel, T. M. (2015) · Pattern Recognition Letters · doi:10.1016/j.patrec.2015.06.003 · Cited by 16

Deep Learning Overview

Ravanmehr, R., & Mohamadrezaei, R. (2023) · Springer eBooks · doi:10.1007/978-3-031-42559-2_2 · Cited by 17

Act as What You Think: Towards Personalized EEG Interaction Through Attentional and Embedded LSTM Learning

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Advancements in Soil Classification: An In-Depth Analysis of Current Deep Learning Techniques and Emerging Trends

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Combining deep learning and language modeling for segmentation-free OCR from raw pixels

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Scalable Neural Networks for Board Games

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Reducing the Computational Complexity of Two-Dimensional LSTMs

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Recurrent feature propagation and edge skip-connections for automatic abdominal organ segmentation

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Deep and Reinforcement Learning in Virtual Synchronous Generator: A Comprehensive Review

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Metaheuristic Approaches for Modeling and Optimization of FDM Process

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Multi-Dimensional Deep Memory Atari-Go Players for Parameter Exploring Policy Gradients

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Learning deep representations for semantic image parsing: a comprehensive overview

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Space Displacement Localization Neural Networks to locate origin points of handwritten text lines in historical documents

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Comparison of Bernoulli and Gaussian HMMs Using a Vertical Repositioning Technique for Off-Line Handwriting Recognition

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Driver behavioral cloning using deep learning

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Hybrid convolutional neural networks

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Social Media Based Topic Modeling for Smart Campus: A Deep Topical Correlation Analysis Method

Peng, J., Zhou, Y., Sun, X., Su, J., & Ji, R. (2018) · IEEE Access · doi:10.1109/access.2018.2890091 · Cited by 11

Parametric and nonparametric context models: A unified approach to scene parsing

Aliniya, P., & Razzaghi, P. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2018.07.013 · Cited by 11

Consideration of Passenger Interactions for the Prediction of Aircraft Boarding Time

Schultz, M., & Reitmann, S. (2018) · Aerospace · doi:10.3390/aerospace5040101 · Cited by 10

TCMINet: Face Parsing for Traditional Chinese Medicine Inspection via a Hybrid Neural Network With Context Aggregation

Li, X., Yang, D., Wang, Y., Zhang, W., Li, F., & Zhang, W. (2020) · IEEE Access · doi:10.1109/access.2020.2995202 · Cited by 10

Artificial intelligence for pathology

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Hybrid Deep Learning Algorithm for Forecasting SARS-CoV-2 Daily Infections and Death Cases

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Supervised texture segmentation using 2D LSTM networks

Byeon, W., & Breuel, T. M. (2014) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2014.7025887 · Cited by 10

The NoisyOffice Database: A Corpus To Train Supervised Machine Learning Filters For Image Processing

Castro-Bleda, M. J., España-Boquera, S., Pastor-Pellicer, J., & Zamora-Martínez, F. (2019) · The Computer Journal · doi:10.1093/comjnl/bxz098 · Cited by 10

RGB-D Scene Labeling with Multimodal Recurrent Neural Networks

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A Face Based Real Time Communication for Physically and Speech Disabled People

Ann, O. C., Lu, M. V., & Theng, L. B. (2011) · IGI Global eBooks · doi:10.4018/978-1-60960-541-4.ch003 · Cited by 10

Deep Learning and Medical Imaging

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A Hybrid RNN Model for Cursive Offline Handwriting Recognition

Bezerra, B. L. D., Zanchettin, C., & de Andrade, V. B. (2012) · Brazilian Symposium on Neural Networks (SBRN) · doi:10.1109/sbrn.2012.41 · Cited by 8

Vision based supervised restricted Boltzmann machine helps to actuate novel shape memory alloy accurately

Dutta, R., Chen, C., Renshaw, D., & Liang, D. (2021) · Scientific Reports · doi:10.1038/s41598-021-95939-y · Cited by 9

A MDRNN-SVM Hybrid Model for Cursive Offline Handwriting Recognition

Bezerra, B. L. D., Zanchettin, C., & de Andrade, V. B. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33266-1_31 · Cited by 9

Inherently Constraint-Aware Control of Many-Joint Robot Arms with Inverse Recurrent Models

Otte, S., Zwiener, A., & Butz, M. V. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-68600-4_31 · Cited by 8

Distinguishing text/non-text natural images with Multi-Dimensional Recurrent Neural Networks

Lyu, P., Shi, B., Zhang, C., & Bai, X. (2016) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2016.7900256 · Cited by 8

On Using 2D Sequence-to-sequence Models for Speech Recognition

Bahar, P., Zeyer, A., Schlüter, R., & Ney, H. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8682155 · Cited by 8

ADMMiRNN: Training RNN with Stable Convergence via an Efficient ADMM Approach

Tang, Y. H., Kan, Z., Sun, D., Qiao, L., Xiao, J., Lai, Z., & Li, D. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-67661-2_1 · Cited by 9

A combined Convolutional Neural Network and Dynamic Programming approach for text line normalization

Pastor-Pellicer, J., España-Boquera, S., Castro-Bleda, M. J., & Zamora-Martínez, F. (2015) · IAPR International Conference on Document Analysis and Recognition (ICDAR) · doi:10.1109/icdar.2015.7333780 · Cited by 8

A scalable neural network architecture for board games

Schaul, T., & Schmidhuber, J. (2008) · IEEE Conference on Computational Intelligence and Games (CIG) · doi:10.1109/cig.2008.5035662 · 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

Enhancing Sentiment Analysis of Indonesian Tourism Video Content Commentary on TikTok: A FastText and Bi-LSTM Approach

Ariyus, D., Manongga, D. H. F., & Sembiring, I. (2024) · Engineering Technology & Applied Science Research · doi:10.48084/etasr.8859 · Cited by 15

Provably Good Solutions to the Knapsack Problem via Neural Networks of Bounded Size

Hertrich, C., & Skutella, M. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i9.16939 · Cited by 7

SpanMTL: a span-based multi-table labeling for aspect-oriented fine-grained opinion extraction

Xing, Y., Zhu, Y., Fan, W., Zhang, Y., Huang, R., Gu, Z., Ip, W. H., & Yung, K. L. (2022) · Soft Computing · doi:10.1007/s00500-022-07721-5 · Cited by 7

PEDAL: A Power Efficient GCN Accelerator with Multiple DAtafLows

Chen, Y., Khadem, A., He, X. J., Talati, N., Khan, T. A., & Mudge, T. (2023) · Design, Automation, and Test in Europe · doi:10.23919/date56975.2023.10137240 · Cited by 8

DeepScribe: Localization and Classification of Elamite Cuneiform Signs via Deep Learning

Williams, E., Su, G., Schloen, S. R., Prosser, M. C., Paulus, S., & Krishnan, S. (2025) · Journal on Computing and Cultural Heritage · doi:10.1145/3716850 · Cited by 7

A Novel Adaptive Intelligent Ensemble Model for Forecasting Primary Energy Demand

Zhao, W., Zhao, J., Yao, X., Jin, Z., & Wang, P. (2019) · Energies · doi:10.3390/en12071347 · Cited by 7

Empirical Auto-Evaluation of Python Code for Performance Analysis of Transformer Network Using T5 Architecture

Ganguli, I., Bhowmick, R. S., Biswas, S., & Sil, J. (2021) · International Conference on Smart Computing and Communications (ICSCC) · doi:10.1109/icscc51209.2021.9528123 · Cited by 7

Sub-Word Based Mongolian Offline Handwriting Recognition

Fan, D., Gao, G., & Wu, H. (2019) · IAPR International Conference on Document Analysis and Recognition (ICDAR) · doi:10.1109/icdar.2019.00048 · Cited by 7

Fully Context-Aware Video Prediction.Preprint

Byeon, W., Wang, Q., Srivastava, R. K., & Koumoutsakos, P. (2017) · arXiv (Cornell University) · Cited by 8

Unsupervised Video Decomposition using Spatio-temporal Iterative InferencePreprint

Zablotskaia, P., Dominici, E. A., Sigal, L., & Lehrmann, A. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.14727 · Cited by 16

Generating image descriptions with multidirectional 2D long short‐term memory

Li, S., Zhang, J., Guo, Q., Lei, J. W., & Tu, D. (2016) · IET Computer Vision · doi:10.1049/iet-cvi.2015.0473 · Cited by 6

Analysis of Basic-SegNet Architecture with Variations in Training Options

Padalkar, G. R., & Khambete, M. (2019) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-16657-1_68 · Cited by 6

Development of Spatiotemporal Recurrent Neural Network for Modeling of Spatiotemporal Processes

Lu, X., Xu, D., & Liu, W. (2020) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.2967810 · Cited by 6

Deep Voting and Structured Regression for Microscopy Image Analysis

Xie, Y., Xing, F., & Yang, L. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-810408-8.00009-2 · Cited by 6

Neural Networks for Natural Language Processing

Morchid, M. (2019) · Advances in computer and electrical engineering book series · doi:10.4018/978-1-7998-1159-6 · Cited by 6

Multimodal Segmentation of Brain Tumours in Volumetric MRI Scans of the Brain Using Time-Distributed U-Net

Dutta, J., Chakraborty, D., & Mondal, D. (2019) · Advances in intelligent systems and computing · doi:10.1007/978-981-13-9042-5_62 · Cited by 6

Spatial Dependency Networks: Neural Layers for Improved Generative Image ModelingPreprint

Miladinovic, D., Stanić, A., Bauer, S., Schmidhuber, J., & Buhmann, J. M. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.08877 · Cited by 7

Enhancing Decision-Making in New Product Development: Forecasting Technologies Revenues Using a Multidimensional Neural Network

Saade, M., Jneid, M., & Saleh, I. (2020) · Lecture notes in business information processing · doi:10.1007/978-3-030-63396-7_48 · Cited by 5

Hybrid intelligent feature selector framework for darknet traffic classification

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Spectro-Temporal Modelling with Time-Frequency LSTM and Structured Output Layer for Voice Conversion

Li, R., Wu, Z., Ning, Y., Sun, L., Meng, H. M. L., & Cai, L. (2017) · Interspeech (USB) · doi:10.21437/interspeech.2017-1122 · Cited by 5

Illegible Text to Readable Text: An Image-to-Image Transformation using Conditional Sliced Wasserstein Adversarial Networks

Karimi, M., Veni, G., & Yu, Y.-Y. (2020) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw50498.2020.00284 · Cited by 5

Multidimensional Networks

Graves, A. (2012) · Studies in computational intelligence · doi:10.1007/978-3-642-24797-2_8 · Cited by 1

Scaling up multidimensional recurrent neural networks for image segmentation

Romelli, M. (2016)

Cells in multidimensional recurrent neural networks

LeifertGundram, StraußTobias, GrüningTobias, WustlichWelf, & LabahnRoger (2016) · Journal of Machine Learning Research · doi:10.5555/2946645.3007050 · Cited by 11

Multimedia Data Modelling Using Multidimensional Recurrent Neural Networks

He, Z., Gao, S., Xiao, L., Liu, D., & He, H. (2018) · Symmetry · doi:10.3390/sym10090370 · Cited by 2

Recurrent Spatial Transformer NetworksPreprint

Sønderby, S. K., Sønderby, C. K., Maaløe, L., & Winther, O. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1509.05329 · Cited by 38