Fusion: Practice and Applications

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2692-4048ISSN (Online) 2770-0070ISSN (Print)

Micro-Expression Recognition using 3D - CNN

Vishal Dubey , Bhavya Takkar , P. Singh Lamba

Micro-expression comes under nonverbal communication, and for a matter of fact, it appears for minute fractions of a second. One cannot control micro-expression as it tells about our actual state emotionally, even if we try to hide or conceal our genuine emotions. As we know that micro-expressions are very rapid due to which it becomes challenging for any human being to detect it with bare eyes. This subtle-expression is spontaneous, and involuntary gives the emotional response. It happens when a person wants to conceal the specific emotion, but the brain is reacting appropriately to what that person is feeling then. Due to which the person displays their true feelings very briefly and later tries to make a false emotional response. Human emotions tend to last about 0.5 - 4.0 seconds, whereas micro-expression can last less than 1/2 of a second. On comparing micro-expression with regular facial expressions, it is found that for micro-expression, it is complicated to hide responses of a particular situation. Micro-expressions cannot be controlled because of the short time interval, but with a high-speed camera, we can capture one's expressions and replay them at a slow speed. Over the last ten years, researchers from all over the globe are researching automatic micro-expression recognition in the fields of computer science, security, psychology, and many more. The objective of this paper is to provide insight regarding micro-expression analysis using 3D CNN. A lot of datasets of micro-expression have been released in the last decade, we have performed this experiment on SMIC micro-expression dataset and compared the results after applying two different activation functions.

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Doi: https://doi.org/10.54216/FPA.010101

Vol. 1 Issue. 1 PP. 5-13, (2020)

Control of Enviornmental Parametrs in A Greenhouse

Surinder Kaur , Diksha Kumari , Vandana Kumari

This paper concentrates on the sustainable use of energy, water, and raw materials to increase production to meet the demand of a high population with available areas. In this work, a kind of automatically controlled greenhouse system of single-chip microcomputer based on sensors is described. This paper presents the system's hardware structure, working principle and process, and a large number of experiments on the effect of the control system. Five control parameters are chosen to increase the yield of the greenhouse, which can be used in indoor breeding and planting. Control actions are performed on the basis of the fusion of different parameters. For the actuation system, the greenhouse is controlled by relays. The proposed control framework permits sparing costs related to wear minimization and delaying the actuator's life, yet continuing promising execution comes out.  Results and conclusions are derived by methods of simulation results.

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Doi: https://doi.org/10.54216/FPA.010102

Vol. 1 Issue. 1 PP. 14-21, (2020)

Palmprint Recognition Using Fusion of Local Binary Pattern and Histogram of Oriented Gradients

Hardik Agarwal , Kanika Somani , Shivangi Sharma , Prerna Arora , P. Singh Lamba , Gopal Chaudhary

In this paper, unique features of the segmented image samples are extracted by using two major feature extraction techniques: Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG). After this, these features are fused to get more precise and productive outcomes. The average accuracy of the three distinct datasets that were generated using the LBP and HOG features are determined. To calculate the accuracy of the three distinct models, classification techniques like KNN and SVM, are adopted.

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Doi: https://doi.org/10.54216/FPA.010103

Vol. 1 Issue. 1 PP. 22-31, (2020)

Artificial Intelligence enabled virtual sixth sense application for the disabled

Aditya Sharma , Aditya Vats , Shiv Shankar Dash , Surinder Kaur

The sixth sense is a multi-platform app for aiding the people in need, that is, people who are handicapped in the form of lack of speech (dumb), lack of hearing (deaf), lack sight (blind), lack of judicial power to differentiate between objects (visual agnosia) and people suffering from autism (characterized by great difficulty in communicating and forming relationships with other people and in using language and abstract concepts). Our current product implementation is on two platforms, namely, mobile and a web app. The mobile app even works for object detection cases in offline mode. What we want to achieve using this is to make a better world for the people suffering from disabilities as well as an educational end for people with cognitive disabilities using our app. The current implementation deals with object recognition, text to speech, and a speech-to-text converter. The speech-to-text converter and text-to-speech converter utilized the Web Speech API (Application Program Interface) for the website and the mobile platform's text-to- speech and speech-to-text library. The object recognition wouldn't fetch enough use out of a website. Hence, it has been implemented on the mobile app utilizing the Firebase ML toolkit and different pre-trained models, both available offline and online.

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Doi: https://doi.org/10.54216/FPA.010104

Vol. 1 Issue. 1 PP. 32-39, (2020)

Study of Multi-Prime RSA

Surinder Kaur , Shivani Mankotia , Pooja Bharadwaj

This paper studies and analyses the encryption and decryption times of a popular variant of the RSA algorithm, the multi-prime RSA. This algorithm uses more than two prime numbers for the encryption process. In this paper, 3, 4, and 5 prime RSA algorithms have been implemented and studied. The rate of increase of encryption and decryption times concerning the number of primes used is also illustrated and compared graphically.

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Doi: https://doi.org/10.54216/FPA.010105

Vol. 1 Issue. 1 PP. 40-48, (2020)