390 citations · 500 across the 11 of their papers we have counts for
11 papers
Banana Ripeness Level Classification using a Simple CNN Model Trained with Real and Synthetic Datasets
Luis Chuquimarca, Boris Vintimilla, Sergio Velastin
The level of ripeness is essential in determining the quality of bananas. To correctly estimate banana maturity, the metrics of international marketing standards need to be conside…
Video-based Human Action Recognition using Deep Learning: A Review
Hieu H. Pham, Louahdi Khoudour, Alain Crouzil +2
Human action recognition is an important application domain in computer vision. Its primary aim is to accurately describe human actions and their interactions from a previously uns…
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Sarthak Pati, Ujjwal Baid, Brandon Edwards +276
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…
Sparse LiDAR and Stereo Fusion (SLS-Fusion) for Depth Estimationand 3D Object Detection
Nguyen Anh Minh Mai, Pierre Duthon, Louahdi Khoudour +2
The ability to accurately detect and localize objects is recognized as being the most important for the perception of self-driving cars. From 2D to 3D object detection, the most di…
A Unified Deep Framework for Joint 3D Pose Estimation and Action Recognition from a Single RGB Camera
Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour +3
We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from RGB video sequences. Our approach proceeds along two stages. In…
A Deep Learning Approach for Real-Time 3D Human Action Recognition from Skeletal Data
Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour +3
We present a new deep learning approach for real-time 3D human action recognition from skeletal data and apply it to develop a vision-based intelligent surveillance system. Given a…
Learning to Recognize 3D Human Action from A New Skeleton-based Representation Using Deep Convolutional Neural Networks
Huy-Hieu Pham, Louahdi Khoudour, Alain Crouzil +2
Recognizing human actions in untrimmed videos is an important challenging task. An effective 3D motion representation and a powerful learning model are two key factors influencing…
Motorcycle Classification in Urban Scenarios using Convolutional Neural Networks for Feature Extraction
Jorge E. Espinosa, Sergio A. Velastin, John W. Branch
This paper presents a motorcycle classification system for urban scenarios using Convolutional Neural Network (CNN). Significant results on image classification has been achieved u…
Motorcycle detection and classification in urban Scenarios using a model based on Faster R-CNN
Jorge E. Espinosa, Sergio A. Velastin, John W. Branch
This paper introduces a Deep Learning Convolutional Neural Network model based on Faster-RCNN for motorcycle detection and classification on urban environments. The model is evalua…
Skeletal Movement to Color Map: A Novel Representation for 3D Action Recognition with Inception Residual Networks
Huy Hieu Pham, Louahdi Khoudour, Alain Crouzil +2
We propose a novel skeleton-based representation for 3D action recognition in videos using Deep Convolutional Neural Networks (D-CNNs). Two key issues have been addressed: First, h…
Learning and Recognizing Human Action from Skeleton Movement with Deep Residual Neural Networks
Huy-Hieu Pham, Louahdi Khoudour, Alain Crouzil +2
Automatic human action recognition is indispensable for almost artificial intelligent systems such as video surveillance, human-computer interfaces, video retrieval, etc. Despite a…