scholarly journals Real-time GPU implementation of an improved cars, pedestrians and bicycles detection and classification system

2011 ◽  
Author(s):  
Alessandro Moro ◽  
Enzo Mumolo ◽  
Massimiliano Nolich ◽  
Kazunori Umeda
Keyword(s):  
Real Time ◽  
Classification System ◽  
Gpu Implementation

scholarly journals Real-Time Wheat Classification System for Selective Herbicides Using Broad Wheat Estimation in Deep Neural Network

2019 ◽  
Vol 9 (1) ◽  
pp. 153
Author(s):  
Arif Ullah ◽  
Nazri Mohd Nawi ◽  
Anditya Arifianto ◽  
Imran Ahmed ◽  
Muhammad Aamir ◽  
...  
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Classification System ◽  
Deep Neural Network

A Sensing Chair

1999 ◽  
Author(s):  
Hong Z. Tan
Keyword(s):  
Automatic Control ◽  
Real Time ◽  
Classification System ◽  
Tracking System ◽  
Pressure Sensors ◽  
Sensory Systems ◽  
Human Computer Interactions ◽  
Sitting Posture ◽  
Haptic Sensing ◽  
Posture Tracking

Abstract This paper is concerned with how objects in an environment can be made aware of people via haptic sensing. It was motivated by the desire to make our environment “smarter” by providing it with sensory systems similar to our own. The work reported here focuses on an object that is involved in virtually all human-computer interactions, yet has remained sensory-deprived — the chair. A real-time sitting posture classification system has been developed using surface-mounted pressure sensors placed on the seatpan and backrest of a chair. The ultimate goal of this work is to build a robust multi-user sitting-posture tracking system that will have many applications including ergonomics and automatic control of airbag deployment in a car. Challenges for reaching the goal and plans of nature work are discussed.

scholarly journals Application of Auxiliary Classifier Wasserstein Generative Adversarial Networks in Wireless Signal Classification of Illegal Unmanned Aerial Vehicles

2018 ◽  
Vol 8 (12) ◽  
pp. 2664 ◽  
Author(s):  
Caidan Zhao ◽  
Caiyun Chen ◽  
Zeping He ◽  
Zhiqiang Wu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Real Time ◽  
Classification System ◽  
Outdoor Environment ◽  
Classification Model ◽  
Signal Classification ◽  
Generative Adversarial Networks ◽  
Adversarial Networks ◽  
Aerial Vehicles ◽  
Discriminative Model

Recently, many studies have reported on image synthesis based on Generative Adversarial Networks (GAN). However, the use of GAN does not provide much attention on the signal classification problem. In the context of using wireless signals to classify illegal Unmanned Aerial Vehicles (UAVs), this paper explores the feasibility of using GAN to improve the training datasets and obtain a better classification model, thereby improving the accuracy of classification. First, we use the generative model of GAN to generate a large datasets, which does not need manual annotation. At the same time, the discriminative model of GAN is improved to classify the types of signals based on the loss function of the discriminative model. Finally, this model can be used to the outdoor environment and obtain a real-time illegal UAVs signal classification system. Our experiments confirmed that the improvements on the Auxiliary Classifier Generative Adversarial Networks (AC-GANs) by limited datasets achieve excellent results. The recognition rate can reach more than 95% in the indoor environment, and this method is also applicable in the outdoor environment. Moreover, based on the theory of Wasserstein GANs (WGAN) and AC-GANs, a more robust Auxiliary Classifier Wasserstein GANs (AC-WGANs) model is obtained, which is suitable for multi-class UAVs. Through the combination of AC-WGANs and Universal Software Radio Peripheral (USRP) B210 software defined radio (SDR) platform, a real-time UAVs signal classification system is also implemented.

A Real-Time Multi-Label Classification System for Short Videos

2019 ◽  
Author(s):  
Bo Jiang ◽  
Lei Zhou ◽  
Li Lin ◽  
Binbin Xu ◽  
Jiahong Yu ◽  
...  
Keyword(s):  
Real Time ◽  
Classification System
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