Zobrazeno 1 - 10
of 378
pro vyhledávání: '"Pattichis, Marios"'
The paper develops datasets and methods to assess student participation in real-life collaborative learning environments. In collaborative learning environments, students are organized into small groups where they are free to interact within their gr
Externí odkaz:
http://arxiv.org/abs/2405.02317
There is strong interest in developing mathematical methods that can be used to understand complex neural networks used in image analysis. In this paper, we introduce techniques from Linear Algebra to model neural network layers as maps between signa
Externí odkaz:
http://arxiv.org/abs/2402.00261
The paper provides a survey of the development of machine-learning techniques for video analysis. The survey provides a summary of the most popular deep learning methods used for human activity recognition. We discuss how popular architectures perfor
Externí odkaz:
http://arxiv.org/abs/2312.05352
Large-scale training of Convolutional Neural Networks (CNN) is extremely demanding in terms of computational resources. Also, for specific applications, the standard use of transfer learning also tends to require far more resources than what may be n
Externí odkaz:
http://arxiv.org/abs/2207.00672
Autor:
Tapia, Luis Sanchez, Gomez, Antonio, Esparza, Mario, Jatla, Venkatesh, Pattichis, Marios, Celedón-Pattichis, Sylvia, LópezLeiva, Carlos
Publikováno v:
The 19th International Conference on Computer Analysis of Images and Patterns (CAIP), 2021
Speech recognition is very challenging in student learning environments that are characterized by significant cross-talk and background noise. To address this problem, we present a bilingual speech recognition system that uses an interactive video an
Externí odkaz:
http://arxiv.org/abs/2112.13463
Publikováno v:
IEEE Transactions on Image Processing, 25(1):119-133, Jan 2016
The Discrete Periodic Radon Transform (DPRT) has been extensively used in applications that involve image reconstructions from projections. This manuscript introduces a fast and scalable approach for computing the forward and inverse DPRT that is bas
Externí odkaz:
http://arxiv.org/abs/2112.13149
Publikováno v:
IEEE Transactions on Image Processing 26.5 (2017): 2230-2245
The manuscript describes fast and scalable architectures and associated algorithms for computing convolutions and cross-correlations. The basic idea is to map 2D convolutions and cross-correlations to a collection of 1D convolutions and cross-correla
Externí odkaz:
http://arxiv.org/abs/2112.13150
We introduce the problem of detecting a group of students from classroom videos. The problem requires the detection of students from different angles and the separation of the group from other groups in long videos (one to one and a half hours). We u
Externí odkaz:
http://arxiv.org/abs/2112.12217
Face recognition in collaborative learning videos presents many challenges. In collaborative learning videos, students sit around a typical table at different positions to the recording camera, come and go, move around, get partially or fully occlude
Externí odkaz:
http://arxiv.org/abs/2110.13269
We study the problem of detecting talking activities in collaborative learning videos. Our approach uses head detection and projections of the log-magnitude of optical flow vectors to reduce the problem to a simple classification of small projection
Externí odkaz:
http://arxiv.org/abs/2110.07646