ISSN2320-2882
Impact Factor9.17
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Paper Title
A HYBRID CNN-LSTM FRAME WORK FOR REAL-TIME MULTIMODAL DATA CLASSIFICATION
Authors
DR KANIGIRI BHARATHI
Keywords
Multimodal Data Classification, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Hybrid Deep Learning Model, Feature Fusion, Real-Time Processing, Temporal Modeling, Spatial Feature Extraction, Deep Learning, Edge Computing
Abstract
Real-time multimodal data classification has become increasingly important in applications such as healthcare monitoring, intelligent surveillance, human activity recognition, and smart environments. However, effectively capturing both spatial and temporal dependencies from heterogeneous data sources remains a significant challenge. This paper proposes a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) framework for real-time multimodal data classification.
The proposed model leverages CNN layers to extract high-level spatial features from input modalities such as images or sensor signals, while LSTM networks are employed to model temporal dependencies and sequential patterns within the data. A feature fusion mechanism is introduced to integrate multimodal representations, enabling robust and context-aware classification. The architecture is optimized for low-latency inference to support real-time deployment in edge-based systems.
Extensive experiments are conducted on benchmark multimodal datasets to evaluate performance in terms of accuracy, precision, recall, F1-score, and computational efficiency. The results demonstrate that the proposed hybrid CNN-LSTM framework outperforms conventional single-model approaches, achieving improved classification accuracy while maintaining real-time processing capability. The proposed system shows strong potential for deployment in dynamic, real-world environments where multimodal data streams are continuously generated.
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IJCRT — journal style
"A HYBRID CNN-LSTM FRAME WORK FOR REAL-TIME MULTIMODAL DATA CLASSIFICATION", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.14, Issue 2, page no.d390-d400, February 2026, Available :https://ijcrt.org/papers/IJCRT2602390.pdf
APA — 7th edition
BHARATHI, K. (2026). A HYBRID CNN-LSTM FRAME WORK FOR REAL-TIME MULTIMODAL DATA CLASSIFICATION. International Journal of Creative Research Thoughts, 14(2), d390-d400. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602390
MLA — 9th edition
BHARATHI, KANIGIRI. "A HYBRID CNN-LSTM FRAME WORK FOR REAL-TIME MULTIMODAL DATA CLASSIFICATION." International Journal of Creative Research Thoughts, vol. 14, no. 2, 2026, pp. d390-d400, https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602390.
Chicago — 17th, bibliography
BHARATHI, KANIGIRI. "A HYBRID CNN-LSTM FRAME WORK FOR REAL-TIME MULTIMODAL DATA CLASSIFICATION." International Journal of Creative Research Thoughts 14, no. 2 (2026): d390-d400. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602390.
Harvard — author–date
BHARATHI, K. (2026) 'A HYBRID CNN-LSTM FRAME WORK FOR REAL-TIME MULTIMODAL DATA CLASSIFICATION', International Journal of Creative Research Thoughts, 14(2), pp. d390-d400. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602390
IEEE — numbered reference
K. BHARATHI, "A HYBRID CNN-LSTM FRAME WORK FOR REAL-TIME MULTIMODAL DATA CLASSIFICATION," IJCRT, vol. 14, no. 2, pp. d390-d400, Feb. 2026.
Vancouver — biomedical
BHARATHI K. A HYBRID CNN-LSTM FRAME WORK FOR REAL-TIME MULTIMODAL DATA CLASSIFICATION. IJCRT. 2026 Feb;14(2):d390-d400.
AMA — 11th edition
BHARATHI K. A HYBRID CNN-LSTM FRAME WORK FOR REAL-TIME MULTIMODAL DATA CLASSIFICATION. IJCRT. 2026;14(2):d390-d400. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602390
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2602390,
author = {KANIGIRI BHARATHI},
title = {A HYBRID CNN-LSTM FRAME WORK FOR REAL-TIME MULTIMODAL DATA CLASSIFICATION},
journal = {International Journal of Creative Research Thoughts},
volume = {14},
number = {2},
pages = {d390-d400},
year = {2026},
month = {February},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602390}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - BHARATHI, KANIGIRI
TI - A HYBRID CNN-LSTM FRAME WORK FOR REAL-TIME MULTIMODAL DATA CLASSIFICATION
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 14
IS - 2
PY - 2026
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602390
SP - d390-d400
ER -
Issue
Volume 14 Issue 2,
February-2026
Pages : d390-d400
Article Information
- Published In
- International Journal of Creative Research Thoughts — Volume 14, Issue 2, February 2026
- Pages
- d390-d400
- Published
- February 2026
- Registration ID
- IJCRT_301604
- Published Paper ID
- IJCRT2602390
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- NALGONDA, TELANGANA, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 176
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT2602390
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT2602390.pdf
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International Journal of Creative Research Thoughts
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