Multimodal Emotion Recognition using Audio-Video Transformer Fusion with Cross Attention

Autor: R, Joe Dhanith P, Venkatraman, Shravan, Narendra, Modigari, Sharma, Vigya, Malarvannan, Santhosh, Gandomi, Amir H.

Understanding emotions is a fundamental aspect of human communication. Integrating audio and video signals offers a more comprehensive understanding of emotional states compared to traditional methods that rely on a single data source, such as speech

Externí odkaz: http://arxiv.org/abs/2407.18552

An Enhanced Focused Web Crawler for Biomedical Topics Using Attention Enhanced Siamese Long Short Term Memory Networks

Autor: Joe Dhanith Pal Nesamony Rose Mary, Surendiran Balasubramanian, Raja Soosaimarian Peter Raj

Publikováno v: Brazilian Archives of Biology and Technology, Vol 64 (2022)

Abstract The Internet is chosen to be one among the primary source of biomedical information. To retrieve necessary biomedical information, the search engine needs an efficient, focused crawler mechanism. But the area of research concerned with the f

Externí odkaz: https://doaj.org/article/554234a305d24a35a15376787df9cf76

A Word Embedding Based Approach for Focused Web Crawling Using the Recurrent Neural Network

Autor: P. R. Joe Dhanith, B. Surendiran, S. P. Raja

Publikováno v: International Journal of Interactive Multimedia and Artificial Intelligence, Vol 6, Iss 6, Pp 122-132 (2021)

Learning-based focused crawlers download relevant uniform resource locators (URLs) from the web for a specific topic. Several studies have used the term frequency-inverse document frequency (TF-IDF) weighted cosine vector as an input feature vector f

Externí odkaz: https://doaj.org/article/b6d3b825161d4713be6c51d09dcf5762

A critical empirical evaluation of deep learning models for solving aspect based sentiment analysis

Autor: P. R. Joe Dhanith, K. S. Sakunthala Prabha

Publikováno v: Artificial Intelligence Review.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1fecbfce75a245d05c774c8ca86868fb
https://doi.org/10.1007/s10462-023-10460-0

A Critique Empirical Evaluation of Relevance Computation for Focused Web Crawlers

Autor: RAJA S P, Dr Surendiran B, Joe Dhanith P R

Publikováno v: Brazilian Archives of Biology and Technology, Vol 64 (2022)
Brazilian Archives of Biology and Technology v.64 2021
Brazilian Archives of Biology and Technology
Instituto de Tecnologia do Paraná (Tecpar)
instacron:TECPAR
Brazilian Archives of Biology and Technology, Volume: 64, Article number: e21210223, Published: 10 JAN 2022

Analogous to the spectacular growth of information-superhighway, The Internet, demands for coherent and economical crawling methods are translucent to shoot up. Consequently, many innovative techniques have been put forth for efficient crawling. Amon

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5dbd872c8b8fee7f1263efe2733db4d8
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132021000101301&tlng=en