1 |
Face Biometric Spoof Detection Method Using a Remote Photoplethysmography Signal
|
|
|
|
In: Sensors; Volume 22; Issue 8; Pages: 3070 (2022)
|
|
BASE
|
|
Show details
|
|
2 |
A Portable Sign Language Collection and Translation Platform with Smart Watches Using a BLSTM-Based Multi-Feature Framework
|
|
|
|
In: Micromachines; Volume 13; Issue 2; Pages: 333 (2022)
|
|
BASE
|
|
Show details
|
|
3 |
American Sign Language Words Recognition of Skeletal Videos Using Processed Video Driven Multi-Stacked Deep LSTM
|
|
|
|
In: Sensors; Volume 22; Issue 4; Pages: 1406 (2022)
|
|
BASE
|
|
Show details
|
|
4 |
Phonemic interference in short-term memory contributes to forgetting but is not due to overwriting
|
|
|
|
In: Test Series for Scopus Harvesting 2021 (2022)
|
|
BASE
|
|
Show details
|
|
5 |
Deep Learning Methods for Human Behavior Recognition
|
|
Lu, Jia. - : Auckland University of Technology, 2021
|
|
BASE
|
|
Show details
|
|
6 |
Auditory and visual short-term memory: Influence of material type, contour, and musical expertise
|
|
|
|
In: ISSN: 0340-0727 ; EISSN: 1430-2772 ; Psychological Research ; https://hal.archives-ouvertes.fr/hal-03384372 ; Psychological Research, Springer Verlag, In press, ⟨10.1007/s00426-021-01519-0⟩ (2021)
|
|
BASE
|
|
Show details
|
|
7 |
Learning emotions latent representation with CVAE for Text-Driven Expressive AudioVisual Speech Synthesis
|
|
|
|
In: ISSN: 0893-6080 ; Neural Networks ; https://hal.inria.fr/hal-03204193 ; Neural Networks, Elsevier, 2021, 141, pp.315-329. ⟨10.1016/j.neunet.2021.04.021⟩ (2021)
|
|
BASE
|
|
Show details
|
|
8 |
Research compendium for Montero-Melis et al. (2021) "No evidence for embodiment: The motor system is not needed to keep action words in working memory" (Cortex) ...
|
|
|
|
BASE
|
|
Show details
|
|
9 |
Cross-cultural cognitive assessment of dementia: a meta-analysis of the impact of illiteracy on dementia screening and an evaluation of a transcultural short-term memory assessment ...
|
|
|
|
BASE
|
|
Show details
|
|
11 |
Human Gait Phase Recognition in Embedded Sensor System
|
|
Liu, Zhenbang. - : KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021
|
|
BASE
|
|
Show details
|
|
12 |
Forecasting Hotel Room Occupancy Using Long Short-Term Memory Networks with Sentiment Analysis and Scores of Customer Online Reviews
|
|
|
|
In: Applied Sciences ; Volume 11 ; Issue 21 (2021)
|
|
BASE
|
|
Show details
|
|
13 |
Dynamic gesture classification of American Sign Language using deep learning
|
|
|
|
Abstract:
American Sign Language (ASL) is a visual method of communication, utilized primarily by the hearing-impaired people. ASL is a sign language with 5 fundamental criterions: state of the hand, location (place of articulation), movement, palm orientation, and facial expressions. Since it is the most well-known gesture-based communication (sign language) of the world, it is essential to address dynamic sign gesture recognition for American Sign Language. To address the static sign language recognition in American Sign language a lot of studies have been done and researchers have claimed approximately 99% accuracy in static sign language recognition. There are very few studies currently available for dynamic gesture recognition in ASL. In this study, a subset of American Sign Language dataset was used, namely World-Level American Sign Language (WLASL) which has originally more than 2000 classes for gesturebased classification of American Sign Language from which we have chosen 100 classes. A combination of VGG16-LSTM, VGG19-LSTM, ResNet101-LSTM, Inception-LSTM and Inception3D based Convolutional Neural Networks (CNN) models were used for extracting spatial and temporal features respectively and applied them on the processed and extracted classes of videos from WLASL dataset. We found our model Inception3D outperformed the Visual Geometry Group-Long Short-Term Memory (VGG-LSTM) architectures, and ResNet101-LSTM models. These models have been compared based on model evaluation metric accuracy, thereby providing suitable insights on model selections. ; Master of Science (MSc) in Computational Sciences
|
|
Keyword:
American sign gestures; convolutional neural network; deep learning; long short-term memory (LSTM
|
|
URL: https://zone.biblio.laurentian.ca/handle/10219/3843
|
|
BASE
|
|
Hide details
|
|
14 |
Asm2Seq: Explainable Assembly Code Functional Summary Generation
|
|
|
|
BASE
|
|
Show details
|
|
15 |
Combination of Time Series Analysis and Sentiment Analysis for Stock Market Forecasting
|
|
|
|
In: Graduate Theses and Dissertations (2021)
|
|
BASE
|
|
Show details
|
|
16 |
Cross-cultural cognitive assessment of dementia: a meta-analysis of the impact of illiteracy on dementia screening and an evaluation of a transcultural short-term memory assessment
|
|
|
|
BASE
|
|
Show details
|
|
17 |
The Effect of Language Recognition in Music on Short-Term Memory Recall and Physiological Stress Response
|
|
|
|
BASE
|
|
Show details
|
|
18 |
The relationship between cognitive ability and BOLD activation across sleep–wake states
|
|
|
|
In: Brain and Mind Institute Researchers' Publications (2021)
|
|
BASE
|
|
Show details
|
|
19 |
Generating Effective Sentence Representations: Deep Learning and Reinforcement Learning Approaches
|
|
|
|
In: Electronic Thesis and Dissertation Repository (2021)
|
|
BASE
|
|
Show details
|
|
20 |
Tipo de erro e nível socioeconômico em tarefa de repetição de não palavras ; Type of error and socioeconomic status in non-word repetition task
|
|
|
|
BASE
|
|
Show details
|
|
|
|