Deep learning for face detection using matlab

This project report presents face detection using Convolutional Neural Network algorithm and Deep Learning combination (DCT / DL) throughout MATLAB simulation and modeling. It reveals that the research project has successfully managed to establish an accurate accurate human face detection and crystal-clear human face recognition systems. The system will annul the face image that are tilted, the images on non-human faces as well as the images of human faces that have watermarks. The test results on face tracking when the image has watermarks. Under this condition, it looks like the CNN and deep learning could not identify the image correctly and wrong result is showing for the second image. This indicates that there is a limitation for the CNN and deep learning algorithm. The disadvantage is, it cannot detects the watermark image, as this image is protected. This process will proceed to Convolutional Neural Network algorithm to identify the human face from a given image. If the image belongs to human features then there will be a tracking box marking clearly the appointed face with a yellow square. This marker will be clearly pointing and shaping a yellowish box of the appointed and selected face or image.The novelty of this research project is that the CNN and deep learning (CNN / DL) methods to trace, scan and detect the human face in a very successful and effective manners taking into account the following distinguished features: the face of the human facing to the front view and not tilted or the face does not make any angles unless angels within 5 to 10 degrees only. The face must not be hiding or nor recognizable or positioned on another object. The face must be real and is not printed on any object like wood or plastic. The water mark must not be printed on the face image picture, otherwise the CNN / DL will not recognize it as human face. The working of the algorithm depends on the deep learning where the system needs to learn the image, identify the faces and store the images into database. By creating a folder called image folder, it will be easy for the MATLAB access into the folder to find the images that content human face and none human face. High resolution for face detection was approximately 85%. The algorithm was able to distinguish between human and non-human faces. By doing this we saved a lot of time in almost half

Impact of Information and Communication Technology (ICT) on construction projects

The changing face of construction projects has resulted in a movement towards the use of technology as a primary means of communication. The consequences of this rise in the use of information and communication technology (ICT) is a loss of interpersonal communication skills. A number of resulting issues within the human – electronic and human – human interfaces are identified in an attempt to define the efficiency of communication in projects. The research shows how ICT effects the social environment of construction project teams and the project outcome. The study seeks to confirm the need for further work in order to develop new forms of communication protocols and behaviour. An initial literature review was undertaken to develop a theoretical review of the impacts of ICT on construction project teams. This review identified a number of issues that were then tested in the field through an observation and two verification interviews. The research confirms the existence of tensions and conflicts in the human – electronic and human - human communication interfaces within the studies environment. It is proposed that the increasing use of ICT occur at the expense of soft system communication. The principal impact of this is a form of ‘human distraction’ which adversely affects the performance of project teams. There is limited theory exploring these issues that suggests the problems identified are not well understood and consequently indicates a gap in knowledge

Will You Look Me in the Eye? The Embrace and Denial of Human Dignity on Marquette Campus

With a foundation in Levinas\u27 pseudo-ethical philosophy of the Phenomena of the Face, this project provided a definition of human dignity and considered whether or not the Marquette University community practices a common respect for human dignity in everyday interactions on the streets of Marquette campus -- focusing in on Wisconsin Avenue due to its constant traffic of both Marquette University students and faculty and Milwaukee community members. This project observed typical day to day interactions that occur while walking around Marquette University\u27s campus with a specific emphasis on how people affiliated with Marquette University react to other Marquette community members as well as members of the Milwaukee community on campus. Ultimately, the research sought to consider the level of awareness Marquette affiliates have upon the subject of human dignity and calls for we as a university to raise awareness about the necessity and nuances of human dignity in everyday interactions.https://epublications.marquette.edu/english_3210ur/1019/thumbnail.jp

FMX (EEPIS FACIAL EXPRESSION MECHANISM EXPERIMENT): PENGENALAN EKSPRESI WAJAH MENGGUNAKAN NEURAL NETWORK BACKPROPAGATION

In the near future, it is expected that the robot can interact with humans. Communication itself has many varieties. Not only from word to word, but body language also be the medium. One of them is using facial expressions. Facial expression in human communication is always used to show human emotions. Whether it is happy, sad, angry, shocked, disappointed, or even relaxed? This final project focused on how to make robots that only consist of head, so it could make a variety facial expression like human beings. This Face Humanoid Robot divided into several subsystems. There are image processing subsystem, hardware subsystem and subsystem of controllers. In image processing subsystem, webcam is used for image data acquisition processed by a computer. This process needs Microsoft Visual C compiler for programming that has been installed with the functions of the Open Source Computer Vision Library (OpenCV). Image processing subsystem is used for recognizing human facial expressions. With image processing, it can be seen the pattern of an object. Backpropagation Neural Network is useful to recognize the object pattern. Subsystem hardware is a Humanoid Robot Face. Subsystem controller is a single microcontroller ATMega128 and a camera that can capture images at a distance of 50 to 120 cm. The process of running the robot is as follows. Images captured by a camera webcam. From the images that have been processed with image processing by a computer, human facial expression is obtained. Data results are sent to the subsystem controller via serial communications. Microcontroller subsystem hardware then ordered to make that facial expression. Result of this final project is all of the subsystems can be integrated to make the robot that can respond the form of human expression. The method used is simple but looks quite capable of recognizing human facial expression. Keyword: OpenCV, Neural Network BackPropagation, Humanoid Robo

Imprints of the thing in itself : Li Zehou's critique of critical philosophy and the historicization of the transcendental

Kant's concept of the "thing in itself" constitutes a formidable challenge to the project of "(anthropological-)historical ontology" with which the name of Li Zehou has become synonymous. Li's radical reinterpretation of Kant's critical philosophy, which locates the conditions of the possibility of knowledge and experience within historical and social evolution and thus seeks to allow for a form of human self-determination, brings us face to face with the dose relation between the epistemological/ontological and normative dimensions of the notion of the thing in itself. My paper attempts to tease out some of the conceptual presuppositions and repercussions of Li's approach to the thing in itself in the Critique of Critical Philosophy (Pipan zhexue zhi pipan), while locating his reading in the broader context of Kant's transcendentalism

Human response to vibration in residential environments (NANR209), Technical report 6 : determination of exposure-response relationships

This technical report presents the development of exposure-response relationships for the human response to vibration in residential environments. The data used to formulate the relationships presented in this report are those which were collected for the Defra funded project “NANR209: Human response to vibration in residential environments”, the main aim of which was the development of exposure-response relationships. Vibration caused by railway traffic, construction work, and internal sources outside of the residents’ control were considered. Response data was collected via face to face interviews with residents in their own homes. The questionnaire was presented as a neighbourhood satisfaction survey and gathered information on, among other things, annoyance caused by vibration and noise exposure. Development and implementation of the questionnaire used for the collection of response data is discussed in Technical Report 2 and Technical Report 5. Vibration exposure was determined via measurement and prediction in such a way that, where possible, an estimation of internal vibration exposure was established for each residence in which a questionnaire was completed. The measurement procedures and methods employed to estimate vibration exposure are detailed in Technical Report 1 and Technical Report 3. Estimations of noise exposure were also derived for each residence using the methods detailed in Technical Report 4