Browsing by Author "Chowdhury, Atiqul Islam"

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An Automated System in ATM Booth Using Face Encoding and Emotion Recognition Process
(ACM International Conference Proceeding Series, 2020) Chowdhury, Atiqul Islam; Shahriar, Mohammad Munem; Islam, Ashraful; Ahmed, Eshtiak; Karim, Asif; Islam, Mohammad Rezwanul
Nowadays, the banking transaction system is more flexible than the previous one. When the banking sector introduces the ATM booth to us, it was a step ahead to ease the human effort. Here, ATM booth is an automated teller machine that gives out money to the consumer by inserting a card in it. All ATM booths support both credit and debit cards for the transaction, and this has saved everyone's time. But still, there are some certain situations, i.e., forgetting the card authentication details for a transaction can ruin a consumer's day. For this reason, this paper has tried to propose a system that will help everyone regarding this situation. This proposed system is about face encoding process with an emotion recognition test for making transactions faster and accurate, based on Convolutional Neural Network (CNN). However, normal card transactions can still be possible besides using the proposed system. FER2013 dataset was used for training and then tested the model using our own sample images. The result shows that the proposed system can correctly separate ‘Happy’ faces from other emotional faces and allow the transaction to proceed.
An Investigation into the Level of Valence Offered By Different Pointing Devices against Challenging Tasks
(International Conference on Advanced Computer Science and Information Systems (ICACSIS), 2020) Ahmed, Eshtiak; Islam, Ashraful; Ashraf, Mohsena; Khan, Md. Ibrahim; Chowdhury, Atiqul Islam; Karim, Asif
Pointing devices are the primary media of interac-tion between humans and computers. The three most popular pointing devices used in computers (both portable and non-portable) are mouse, touchpad and nubs (joystick). They have their different advantages and use cases while being targeted to different user groups. The aim of this study was to investigate whether the aforementioned pointing devices have different effects on human valence. A total of 12 participants were recruited for the experiment. Each participant completed a pointing reaction test with every pointing device aforementioned, where they selected as many randomly appearing circles as possible in a given amount of time. Then, subjective ratings of emotional valence and arousal were collected, and the effects of the pointing device used on these ratings were investigated. Our study shows that the valence rating of using the mouse were significantly higher in challenging scenarios, compared to the likes of touchpad and nub.
hActNET
(Scopus, 2020) Chowdhury, Atiqul Islam; Ashraf, Mohsena; Islam, Ashraful; Ahmed, Eshtiak; Jaman, Md. Saroar; Rahman, Mohammad Masudur
Human activity recognition (HAR) is considered as one of the most difficult and challenging issues now a days. Many experiments are now in progress regarding this problem. Among many human activities, mostly six are considered for research in this area. This activity recognition issue can be measured with the help of smartphones and smartphone sensors, along with the connection of Internet of Things (IoT) devices. In this research, an improved deep learning scheme is proposed for the recognition of human activities. A customized Neural Network (NN) model was designed and tested for the research. The proposed model obtained 96.47% accuracy on the HAR with smartphones dataset that is better than most other analyzed models. Sensors such as accelerometer, gyroscope are focused on the data analysis portion of this research work. This article will give a clear idea of the dataset, Machine Learning algorithms, and the effect of the proposed algorithm.
Robo-Friend
(Scopus, 2021) Ahmed, Eshtiak; Islam, Ashraful; Chowdhury, Atiqul Islam; Rahman, Mohammad Masudur
Social robots are becoming more popular every day because of their resemblance with human behavior and interaction styles. They should be treated more like companions rather than just a fancy source of entertainment. Recent studies have shown great promise for robots to act as teachers, companions, caregivers and so on. In this study, primarily, a feasibility analysis is done to find out the way how a social robot can be used as a companion where it can sense the emotions of the users, empathize with their feelings and provide feedback with a view to changing their mood. A context study was conducted to make design implications where user experience goals such as inspiration, sense of control, relaxation, accomplishment and confidence were considered in the implementation. Furthermore, a prototype was designed based on a social robot, Pepper which then was interacted with potential users, either in groups or individually. The results support the fact that, a well-implemented social robot can effectively empathize with human users’ emotions.