Export Citations
Save this search
Please login to be able to save your searches and receive alerts for new content matching your search criteria.
- research-articleMay 2024
Fast Recurrent Neural Network with Bi-LSTM for Handwritten Tamil Text Segmentation in NLP
ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Volume 23, Issue 5Article No.: 68, Pages 1–20https://doi.org/10.1145/3643808Tamil text segmentation is a long-standing test in language comprehension that entails separating a record into adjacent pieces based on its semantic design. Each segment is important in its own way. The segments are organised according to the purpose of ...
- research-articleNovember 2023
Bio-inspired algorithm-based hyperparameter tuning for drug-target binding affinity prediction in healthcare
Intelligent Decision Technologies (INTDTEC), Volume 17, Issue 42023, Pages 1455–1474https://doi.org/10.3233/IDT-230145The greatest challenge for healthcare in drug repositioning and discovery is identifying interactions between known drugs and targets. Experimental methods can reveal some drug-target interactions (DTI) but identifying all of them is an expensive and ...
- research-articleJanuary 2023
SMedia: social media data analysis for emergency detection and its type identification
International Journal of Computational Science and Engineering (IJCSE), Volume 26, Issue 42023, Pages 385–396https://doi.org/10.1504/ijcse.2023.132178Due to the advancement of technology, social media can spread information very fast. People post information about themselves or about an event in the proximity of any emergency. However, proper analysis of social media data is necessary to address the ...
- research-articleJanuary 2023
Sensor-enabled biometric signature-based authentication method for smartphone users
International Journal of Biometrics (IJOB), Volume 15, Issue 22023, Pages 212–232https://doi.org/10.1504/ijbm.2023.129229With the ubiquity of smartphones, the need for foolproof authentication mechanisms that support 'authentication on the go' and remote authentication is on the rise. Signature being the most sophisticated authentication method, this paper explores idea of ...
- research-articleNovember 2022
Static and Dynamic Isolated Indian and Russian Sign Language Recognition with Spatial and Temporal Feature Detection Using Hybrid Neural Network
- E. Rajalakshmi,
- R. Elakkiya,
- Alexey L. Prikhodko,
- M. G. Grif,
- Maxim A. Bakaev,
- Jatinderkumar R. Saini,
- Ketan Kotecha,
- V. Subramaniyaswamy
ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Volume 22, Issue 1Article No.: 26, Pages 1–23https://doi.org/10.1145/3530989The Sign Language Recognition system intends to recognize the Sign language used by the hearing and vocally impaired populace. The interpretation of isolated sign language from static and dynamic gestures is a difficult study field in machine vision. ...
-
- research-articleJanuary 2022
An intelligent fuzzy and IoT-aware air quality prediction and monitoring system using CRF and Bi-LSTM
International Journal of Intelligent Engineering Informatics (IJIEI), Volume 10, Issue 52022, Pages 379–396https://doi.org/10.1504/ijiei.2022.129095Recently, air pollution has been increasing drastically in the majority of metropolitan cities around the world. This is necessary to reduce air pollution, and we propose a new air quality prediction system to predict air quality and pollution levels in ...
- research-articleMay 2021
Incorporating Hand-crafted Features in a Neural Network Model for Stance Detection on Microblog
ICCIP '20: Proceedings of the 6th International Conference on Communication and Information ProcessingNovember 2020, Pages 57–64https://doi.org/10.1145/3442555.3442565Microblogs, especially twitter, has made unprecedented opportunities for users to assert their stance towards various entities, issues, and events. Analyzing user stances from tweets provide opportunities to various organizations for decision making. ...
- research-articleJanuary 2021
A Novel Deep-Learning-Based Model for Medical Text Classification
ICCPR '20: Proceedings of the 2020 9th International Conference on Computing and Pattern RecognitionOctober 2020, Pages 267–273https://doi.org/10.1145/3436369.3436469In recent years, with development of the Internet hospitals and natural language processing technology, intelligent medical guidance based on machine learning has been gained increasing attentions. Medical text classification is indispensable for ...
- research-articleJanuary 2021
Extraction of drug-drug interaction information using a deep neural network
International Journal of Data Mining and Bioinformatics (IJDMB), Volume 25, Issue 3-42021, Pages 181–200https://doi.org/10.1504/ijdmb.2021.122855The information about Drug-Drug Interaction (DDI) is available in biomedical literature and extraction of this information manually is an extremely challenging and arduous task. DDI information helps medical practitioners to suggest various combination of ...
- research-articleDecember 2019
AB-LSTM: Attention-based Bidirectional LSTM Model for Scene Text Detection
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 15, Issue 4Article No.: 107, Pages 1–23https://doi.org/10.1145/3356728Detection of scene text in arbitrary shapes is a challenging task in the field of computer vision. Most existing scene text detection methods exploit the rectangle/quadrangular bounding box to denote the detected text, which fails to accurately fit text ...
- research-articleMarch 2019
Towards Enabling Feedback on Rhetorical Structure with Neural Sequence Models
LAK19: Proceedings of the 9th International Conference on Learning Analytics & KnowledgeMarch 2019, Pages 310–319https://doi.org/10.1145/3303772.3303808Analysis of student writing, both for assessment and for enabling feedback have been of interest to the field of learning analytics. While much progress can be made through detection of local cues in writing, structured prediction approaches offer ...
- abstractJuly 2018
Anomaly detection for drinking water quality via deep biLSTM ensemble
GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference CompanionJuly 2018, Pages 3–4https://doi.org/10.1145/3205651.3208203In this paper, a deep BiLSTM ensemble method was proposed to detect anomaly of drinking water quality. First, a convolutional neural network (CNN) is utilized as a feature extractor in order to process the raw data of water quality. Second, ...
- research-articleMarch 2018
A topic BiLSTM model for sentiment classification
ICIAI '18: Proceedings of the 2nd International Conference on Innovation in Artificial IntelligenceMarch 2018, Pages 143–147https://doi.org/10.1145/3194206.3194240The Long Short Term Memory (LSTM) network is very effective for capturing sequence information which can help to analyze sentiments. However, it fails to capture the meaning of polysemous word under different contexts. In this paper, we propose topic ...
- research-articleDecember 2016
Effective attention-based neural architectures for sentence compression with bidirectional long short-term memory
SoICT '16: Proceedings of the 7th Symposium on Information and Communication TechnologyDecember 2016, Pages 123–130https://doi.org/10.1145/3011077.3011111We propose a novel model that apply an extension of the Long Short-Term Memory neural network for sentence compression task. In our model, only the most relevant context of each word is concentrated to avoid the redundant information. Our model is based ...