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Automatic Hierarchical Attention Neural Network for Detecting AD

Yilin Pan, Bahman Mirheidari, Markus Reuber, Annalena Venneri, Daniel Blackburn, Heidi Christensen
2019 Interspeech 2019  
Picture description tasks are used for the detection of cognitive decline associated with Alzheimer's disease (AD).  ...  This outperforms baseline models, including bidirectional LSTM and bidirectional hierarchical neural network without an attention mechanism, and demonstrate that the use of hierarchical models with attention  ...  Acknowledgements This work is supported under the European Unions H2020 Marie Skodowska-Curie programme TAPAS (Training Network for PAthological Speech processing; Grant Agreement No. 766287).  ... 
doi:10.21437/interspeech.2019-1799 dblp:conf/interspeech/PanMRVBC19 fatcat:nsker245dra4lo75xdmvx4o3em

A Survey on Vision Based Approaches for Image Description

Akanksha P. Deshmukh, Dr. Ghotkar A. S.
2017 IJARCCE  
This paper contains neural network appproaches for generating description of images, process of image decription, identified dataset and technolgies used for this framework and various evaluation metrics  ...  used for calculating scores. 192 and speed in building your scientific algorithms while making the process extremely simple.  ...  Then used a Multimodal Recurrent Neural Network (MRNN) architecture that uses the inferred alignments to learn to generate novel descriptions of image regions.  ... 
doi:10.17148/ijarcce.2017.6435 fatcat:wocqsvspwvhpngpti24jtktqku

Identifying the concept of Image and Captioning Using Deep Neural Networks

2020 International Journal of Advanced Trends in Computer Science and Engineering  
Convolutional Neural Network (CNN) implicitly extract features from the image, and Recurrent Neural Network is used for sentence generation.  ...  Image captioning automatically generates the textual description consistent with the content observed in a picture, and it is the mixture of two methods, including computer vision and natural language  ...  [9] Multimodal Recurrent Neural Network(M-RNN) The architecture of the multimodal Recurrent Neural Network (M-RNN) is shown below.  ... 
doi:10.30534/ijatcse/2020/204952020 fatcat:m2f2pppub5go7eh7uqisqjxbry

A Neural Approach to Automated Essay Scoring

Kaveh Taghipour, Hwee Tou Ng
2016 Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing  
We explore several neural network models for the task of automated essay scoring and perform some analysis to get some insights of the models.  ...  In this paper, we develop an approach based on recurrent neural networks to learn the relation between an essay and its assigned score, without any feature engineering.  ...  We are also grateful to the anonymous reviewers for their helpful comments.  ... 
doi:10.18653/v1/d16-1193 dblp:conf/emnlp/TaghipourN16 fatcat:o42oskwlazcq7d7czponyxdhqq

Automatic Image Captioning Using Neural Networks

Subash Pandey, Rabin Kumar Dhamala, Bikram Karki, Saroj Dahal, Rama Bastola
2020 Journal of Innovations in Engineering Education  
Image is passed to Convolutional Neural Network (CNN) encoder and the output from it is fed further to Recurrent Neural Network (RNN) decoder that generates meaningful captions.  ...  To evaluate the model performance, we used BLEU (Bilingual Evaluation Understudy) score and match predicted words to the original caption.  ...  Figure 1 : 1 Image feature extraction and encoding 3) Decoder: LSTM (Long Short-Term Memory) network is used as a decoder to give a decoded RNN (Recurrent Neural Network) <start> token indicates the start  ... 
doi:10.3126/jiee.v3i1.34335 fatcat:puuouha3crd7vofnxwkb7hpcnq

DFKI-MLT System Description for the WMT18 Automatic Post-editing Task

Daria Pylypenko, Raphael Rubino
2018 Proceedings of the Third Conference on Machine Translation: Shared Task Papers  
Three monolingual neural sequenceto-sequence APE systems were trained using target-language data only: one using an attentional recurrent neural network architecture and two using the attention-only (transformer  ...  We made use of the provided training sets only and trained APE models applicable to phrase-based and neural MT outputs.  ...  Responsibility for the content of this publication is with the authors.  ... 
doi:10.18653/v1/w18-6469 dblp:conf/wmt/PylypenkoR18 fatcat:bh7xcqh2p5d75kel37jhqm6phe

An Efficient Technique for Image Captioning using Deep Neural Network [article]

Borneel Bikash Phukan, Amiya Ranjan Panda
2020 arXiv   pre-print
Every entity in internet must be properly identified and managed and therefore in the case of image data, automatic captioning for identification is required.  ...  This paper discusses an efficient and unique way to perform automatic image captioning on individual image and discusses strategies to improve its performances and functionalities.  ...  Hence, the goal of this paper is to describe an efficient method to automatically generate caption for an image using deep neural network approach.  ... 
arXiv:2009.02565v1 fatcat:q6vfq6vctrgjroh2xpy2ochlzq

Image Captioning Algorithm Based on Multi-Branch CNN and Bi-LSTM

Shan HE, Yuanyao LU, Shengnan CHEN
2021 IEICE transactions on information and systems  
In this paper, the multi-branch deep convolutional neural network is used as the encoder to extract image features, and the recurrent neural network is used to generate descriptive text that matches the  ...  The image captioning task combines cutting-edge methods in two fields. By building an end-to-end encoder-decoder model, its description performance can be greatly improved.  ...  They use pre-trained convolutional neural networks (such as VGG or ResNet) as encoders, and use recurrent neural networks as language models. (2) Softattention and hard attention methods [19] introduce  ... 
doi:10.1587/transinf.2020edp7227 fatcat:45tq63dubffjrey47fkrlk6y6u

Natural language description of images using hybrid recurrent neural network

Md. Asifuzzaman Jishan, Khan Raqib Mahmud, Abul Kalam Al Azad
2019 International Journal of Electrical and Computer Engineering (IJECE)  
Our Hybrid Recurrent Neural Network model is based on the intricacies of Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Bi-directional Recurrent Neural Network (BRNN) models.  ...  We presented a learning model that generated natural language description of images.  ...  images using hybrid recurrent neural network (Md.  ... 
doi:10.11591/ijece.v9i4.pp2932-2940 fatcat:bq54iflbxreh3ombqzeoxmx3k4

Fully automatic scoring of handwritten descriptive answers in Japanese language tests [article]

Hung Tuan Nguyen, Cuong Tuan Nguyen, Haruki Oka, Tsunenori Ishioka, Masaki Nakagawa
2022 arXiv   pre-print
This paper presents an experiment of automatically scoring handwritten descriptive answers in the trial tests for the new Japanese university entrance examination, which were made for about 120,000 examinees  ...  These results are promising for further research on end-to-end automatic scoring of descriptive answers.  ...  The current advanced text recognition methods, such as convolutional recurrent neural network (CRNN), exhibits poor performance on the proposed SCUT-EPT dataset.  ... 
arXiv:2201.03215v1 fatcat:huavc5bd7nh3rgqgdqhineavgq

End-to-End Language Identification Using Attention-Based Recurrent Neural Networks

Wang Geng, Wenfu Wang, Yuanyuan Zhao, Xinyuan Cai, Bo Xu
2016 Interspeech 2016  
This paper proposes a novel attention-based recurrent neural network (RNN) to build an end-to-end automatic language identification (LID) system.  ...  Thirdly, a hybrid test method which traverses all gold labels is adopted in the inference phase.  ...  Figure 1 : The Architecture of attention-based recurrent neural network.  ... 
doi:10.21437/interspeech.2016-686 dblp:conf/interspeech/GengWZCX16 fatcat:mb7dstvz5jfaxgqv7cr7yco32q

Popular Song Composition Based on Deep Learning and Neural Network

Jun Kuang, Tingfeng Yang, Naeem Jan
2021 Journal of Mathematics  
Then, the neural network model is constructed, using the memory function of the cyclic neural network and the characteristics of processing sequence data, the piano notes are combined into a sequence according  ...  to the musical theory rules, and the neural network model automatically learns this rule and then generates the note sequence.  ...  Recurrent Neural Network Structure.  ... 
doi:10.1155/2021/7164817 fatcat:iwd4kd53xjhi3jvhglhgzllvx4

Simple Image Description Generator via a Linear Phrase-Based Approach [article]

Remi Lebret and Pedro O. Pinheiro and Ronan Collobert
2015 arXiv   pre-print
Based on caption syntax statistics, we propose a simple language model that can produce relevant descriptions for a given test image using the phrases inferred.  ...  We train a purely bilinear model that learns a metric between an image representation (generated from a previously trained Convolutional Neural Network) and phrases that are used to described them.  ...  ACKNOWLEDGEMENTS This work was supported by the HASLER foundation through the grant "Information and Communication Technology for a Better World 2020" (SmartWorld).  ... 
arXiv:1412.8419v3 fatcat:egazplijuzexlpi2sstxcj2j6m

Discovering Inconsistencies between Requested Permissions and Application Metadata by using Deep Learning

Huseyin Alecakir, Muhammet Kabukcu, Burcu Can, Sevil Sen
2020 2020 International Conference on Information Security and Cryptology (ISCTURKEY)  
This study proposes a new method based on natural language processing and recurrent neural networks.  ...  The experimental results show that high precision is obtained by the proposed solution, and the proposed method could be used for triage of Android applications.  ...  In this paper, we use natural language processing methods, as well as recurrent neural networks to tackle the description-tofdelity problem in Android applications.  ... 
doi:10.1109/iscturkey51113.2020.9308004 fatcat:76inem5ovvef7gyk54xtyltjjm

Attention-Based Deep Learning Model for Image Captioning: A Comparative Study

Phyu Phyu Khaing, University of Computer Studies, Mandalay, Myanmar, May The` Yu
2019 International Journal of Image Graphics and Signal Processing  
This also discusses the datasets for image captioning and the evaluation metrics to test the accuracy.  ...  Image captioning by applying deep learning model can enhance the description accuracy. Attention mechanisms are the upward trend in the model of deep learning for image caption generation.  ...  Bidirectional recurrent neural network (BiRNN) was implemented for an encoder and recurrent neural network learning model (RNN-LM) based on attention was used for a decoder in the neural translation  ... 
doi:10.5815/ijigsp.2019.06.01 fatcat:j5xryx3frva3jm7htrpbmpjvsu
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