Temporal Reasoning Graph for Activity Recognition

Registration ID: IJNRD_181208

Published ID: IJNRD2205003

DOI: Click Here to Get

Sonali Digambar Chandole , Sanjay Pingat

Convolutional neural networks (CNNs), LSTM, Human activity

In this work, we expect to resolve the issue of human cooperation acknowledgment in recordings by investigating the long haul between related elements among various people. As of late, Long Short-Term Memory (LSTM) has gotten a well-known decision to display singular dynamic for single-individual activity acknowledgment because of its capacity to catch the transient movement data in a reach. In any case, most existing LSTM-based techniques center just on catching the elements of human collaboration by basically consolidating all elements of people or demonstrating them in general. Such strategies disregard the between related elements of how human cooperation’s change after some time. To this end, we propose a novel various leveled Long Short-Term Concurrent Memory (H-LSTCM) to model the drawn out between related elements among a gathering of people for perceiving human connections. In particular, we first feed every individual's .Static highlights into a Single-Person LSTM to show the single-individual dynamic. Consequently, at one time step, the yields of all Single-Person LSTM units are taken care of into a novel Concurrent LSTM (Co-LSTM) unit, which predominantly comprises of numerous sub-memory units, another cell door, furthermore, another co-memory cell. In the Co-LSTM unit, each sub-memory unit stores singular movement data, while this Co-LSTM unit specifically coordinates and stores between related movement data between different communicating people from various sub-memory units by means of the cell door and co-memory cell, individually. Broad investigations on a few public datasets approve the viability of the proposed H-LSTCM by contrasting against standard and cutting edge strategies.

Published Paper   E-Certificate

Sonali Digambar Chandole & Sanjay Pingat (May-2022). Temporal Reasoning Graph for Activity Recognition. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(5), 24-33. https://ijnrd.org/papers/IJNRD2205003.pdf

Volume 7 Issue 5, May-2022

Pages : 24-33

Paper Reg. ID: IJNRD_181208

Published Paper Id: IJNRD2205003

Downloads: 000121982

Research Area: Computer Science & Technology 

Country: Solapur, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2205003.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2205003

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave | IJNRD.ORG | IJNRD.COM | IJPUB.ORG

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

The INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to advance applied, theoretical, and experimental research across diverse fields. Its goal is to promote global scientific information exchange among researchers, developers, engineers, academicians, and practitioners. IJNRD serves as a platform where educators and professionals can share research evidence, models of best practice, and innovative ideas, contributing to academic growth and industry relevance.

Indexing Coverage includes Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar (AI-Powered Research Tool), Microsoft Academic, Academia.edu, arXiv.org, ResearchGate, CiteSeerX, ResearcherID (Thomson Reuters), Mendeley, DocStoc, ISSUU, Scribd, and many more recognized academic repositories.

How to submit the paper?

By Our website

Click Here to Submit Paper Online

By Mail

Send your paper to editor@ijnrd.org

Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: IJNRD is an International Peer-reviewed, Refereed, and Open Access Journal with Transparent Peer Review as per the new UGC CARE 2025 guidelines, offering low-cost multidisciplinary publication with Crossref DOI and global indexing.

Subject Category: Research Area

Call for Paper: More Details