Adversarial Patches-based Attacks on Automated Vehicle Make and Model Recognition Systems

The difficulty in class student state recognition is how to make feature judgments based on student facial expressions and movement state. At present, some intelligent models are not accurate in class student state recognition. In order to improve the model recognition effect, this study builds a two-level state detection framework based on deep learning and HMM feature recognition algorithm, and expands it as a multi-level detection model through a reasonable state classification method. In addition, this study selects continuous HMM or deep learning to reflect the dynamic generation characteristics of fatigue, and designs random human fatigue recognition experiments to complete the collection and preprocessing of EEG data, facial video data, and subjective evaluation data of classroom students. In addition to this, this study discretizes the feature indicators and builds a student state recognition model. Finally, the performance of the algorithm proposed in this paper is analyzed through experiments. The research results show that the algorithm proposed in this paper has certain advantages over the traditional algorithm in the recognition of classroom student state features.

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View Independent Vehicle Make and Model Recognition with Virtual Frontal View

IEEJ Transactions on Electronics Information and Systems ◽

10.1541/ieejeiss.134.233 ◽

2014 ◽

Vol 134 (2) ◽

pp. 233-241

Author(s):

Yukiko Shinozuka ◽

Takuya Minagawa ◽

Hideo Saito

Keyword(s):

Frontal View ◽

Model Recognition

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Alternate Trajectory Determination Using Multimode Automated Robotic Vehicle with Line Following and Object Following Mode

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v8i3.593 ◽

2018 ◽

Vol 8 (3) ◽

pp. 46

Author(s):

Varun Kumar ◽

Lakshya Gaur ◽

Arvind Rehalia

Keyword(s):

Ultrasonic Sensor ◽

Robotic Assembly ◽

Voltage Regulator ◽

Automated Vehicle ◽

Dc Motors ◽

Arduino Uno ◽

Robotic Vehicle ◽

Line Following ◽

Selection Of ◽

Trajectory Determination

In this paper the authors have explained the development of robotic vehicle prepared by them, which operates autonomously and is not controlled by the users, except for selection of modes. The different modes of the automated vehicle are line following, object following and object avoidance with alternate trajectory determination. The complete robotic assembly is mounted on a chassis comprising of Arduino Uno, Servo motors, HC-SRO4 (Ultrasonic sensor), DC motors (Geared), L293D Motor Driver, IR proximity sensors, Voltage Regulator along with castor wheel and two normal wheels.

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Human Ear Pattern Recognition System

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i8.35 ◽

2017 ◽

Vol 7 (8) ◽

pp. 117 ◽

Cited By ~ 1

Author(s):

V. Jagan Naveen ◽

K. Krishna Kishore ◽

P. Rajesh Kumar

Keyword(s):

Pattern Recognition ◽

Expectation Maximization Algorithm ◽

Recognition System ◽

Modern World ◽

Person Identification ◽

Biometric Systems ◽

Different Types ◽

Recognition Systems ◽

Human Ear ◽

Pca Algorithm

In the modern world, human recognition systems play an important role to improve security by reducing chances of evasion. Human ear is used for person identification .In the Empirical study on research on human ear, 10000 images are taken to find the uniqueness of the ear. Ear based system is one of the few biometric systems which can provides stable characteristics over the age. In this paper, ear images are taken from mathematical analysis of images (AMI) ear data base and the analysis is done on ear pattern recognition based on the Expectation maximization algorithm and k means algorithm. Pattern of ears affected with different types of noises are recognized based on Principle component analysis (PCA) algorithm.

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Real Time Automated Vehicle Monitoring and Control System Using Internet of Vehicles

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v6i3.491494 ◽

2018 ◽

Vol 6 (3) ◽

pp. 491-494

Author(s):

Nalina V. ◽

◽

P. Jayarekha ◽

Keyword(s):

Control System ◽

Real Time ◽

Monitoring And Control ◽

Monitoring And Control System ◽

Internet Of Vehicles ◽

Automated Vehicle ◽

Vehicle Monitoring ◽

And Control

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Facial recognition technologies and the new physiognomic era

Kritische Lebenskunst - psychosozial ◽

10.30820/0171-3434-2020-2-45 ◽

2020 ◽

Vol 43 (2) ◽

pp. 45-56

Author(s):

Abigail Nieves Delgado

Keyword(s):

Facial Recognition ◽

Personal Identification ◽

Digital Photographs ◽

Different Types ◽

Recognition Systems ◽

The Way

The current overproduction of images of faces in digital photographs and videos, and the widespread use of facial recognition technologies have important effects on the way we understand ourselves and others. This is because facial recognition technologies create new circulation pathways of images that transform portraits and photographs into material for potential personal identification. In other words, different types of images of faces become available to the scrutiny of facial recognition technologies. In these new circulation pathways, images are continually shared between many different actors who use (or abuse) them for different purposes. Besides this distribution of images, the categorization practices involved in the development and use of facial recognition systems reinvigorate physiognomic assumptions and judgments (e.g., about beauty, race, dangerousness). They constitute the framework through which faces are interpreted. This paper shows that, because of this procedure, facial recognition technologies introduce new and far-reaching »facialization« processes, which reiterate old discriminatory practices.

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