Earnest Paul Ijjina

According to our database1, Earnest Paul Ijjina authored at least 13 papers between 2014 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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PhD thesis 
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Bibliography

2019
Accident detection from dashboard camera video.
Proceedings of the 10th International Conference on Computing, 2019

Computer Vision-based Accident Detection in Traffic Surveillance.
Proceedings of the 10th International Conference on Computing, 2019

2017
Human action recognition in RGB-D videos using motion sequence information and deep learning.
Pattern Recognit., 2017

2016
Classification of human actions using pose-based features and stacked auto encoder.
Pattern Recognit. Lett., 2016

Human action recognition using genetic algorithms and convolutional neural networks.
Pattern Recognit., 2016

Hybrid deep neural network model for human action recognition.
Appl. Soft Comput., 2016

2015
Human action recognition based on motion capture information using fuzzy convolution neural networks.
Proceedings of the Eighth International Conference on Advances in Pattern Recognition, 2015

2014
Facial Expression Recognition Using Kinect Depth Sensor and Convolutional Neural Networks.
Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

One-Shot Periodic Activity Recognition Using Convolutional Neural Networks.
Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks.
Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

Human Action Recognition Based on MOCAP Information Using Convolution Neural Networks.
Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

Human Action Recognition Using Action Bank Features and Convolutional Neural Networks.
Proceedings of the Computer Vision - ACCV 2014 Workshops, 2014

View and Illumination Invariant Object Classification Based on 3D Color Histogram Using Convolutional Neural Networks.
Proceedings of the Computer Vision - ACCV 2014 Workshops, 2014


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