Deep q-network (DQN) partialocclusion segmentation and Backtracking search optimization algorithm (BSOA) with optical Flow reconstruction for facial expression emotion recognition (Record no. 22703)
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| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250424094408.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250424b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 25966 |
| Author | Sudha, S. S. |
| 245 ## - TITLE STATEMENT | |
| Title | Deep q-network (DQN) partialocclusion segmentation and Backtracking search optimization algorithm (BSOA) with optical Flow reconstruction for facial expression emotion recognition |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.15(2), Oct |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Chennai |
| Name of publisher, distributor, etc. | ICT Academy |
| Year | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 3473-3481p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Video facial expression recognition (FER) has garnered a lot of<br/>attention recently and is helpful for several applications. Although<br/>many algorithms demonstrate impressive performance in a controlled<br/>environment without occlusion, identification in the presence of partial<br/>facial occlusion remains a challenging issue. Solutions based on<br/>reconstructing the obscured area of the face have been suggested as a<br/>way to deal with occlusions. These options mostly rely on the face’s<br/>shape or texture. Nonetheless, the resemblance in facial expressions<br/>among individuals appears to be a valuable advantage for the<br/>reconstruction. For semantic segmentation based on occlusions,<br/>Reinforcement Learning (RL) is introduced as the initial stage. From<br/>a pool of unlabeled data, an agent learns a policy to choose a subset of<br/>tiny informative image patches to be tagged instead of full images. In<br/>the second stage, a trained Backtracking Search Algorithm (BSA) is<br/>used to rebuild optical flows that have been distorted by the occlusion.<br/>On obtaining optical flows estimated from occluded facial frames, AEs<br/>restore optical flows of occluded regions. These recovered optical flows<br/>become inputs to anticipate classes f expressions. Optical flux<br/>reconstructions then classify stages. This study evaluates classification<br/>model’s performances for face expression identification based on Very<br/>Deep Convolution Networks (VGGNet). Furthermore, it produces more<br/>accurate confusion matrices and proposes approaches for the KMU-<br/>FED and CK+ databases, respectively. The results are evaluated using<br/>metrics including recall, f-measure, accuracy, and precision. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 4622 |
| Topical term or geographic name entry element | Computer Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 25967 |
| Co-Author | Suganya, S. S. |
| 773 0# - HOST ITEM ENTRY | |
| Place, publisher, and date of publication | Chennai ICT Academy |
| Title | ICTACT Journal on Soft Computing (IJSC) |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | https://ictactjournals.in/paper/IJSC_Vol_15_Iss_2_Paper_12_3556_3566.pdf |
| Link text | Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Articles Abstract Database |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | School of Engineering & Technology | School of Engineering & Technology | Archieval Section | 24/04/2025 | 2025-0652 | 24/04/2025 | 24/04/2025 | Articles Abstract Database |