Digital Commons Network^™

Utilizing Motion And Spatial Features For Sign Language Gesture Recognition Using Cascaded Cnn And Lstm Models, Hamzah Luqman, Elsayed Elalfy

Turkish Journal of Electrical Engineering and Computer Sciences

Sign language is a language produced by body parts gestures and facial expressions. The aim of an automatic sign language recognition system is to assign meaning to each sign gesture. Recently, several computer vision systems have been proposed for sign language recognition using a variety of recognition techniques, sign languages, and gesture modalities. However, one of the challenging problems involves image preprocessing, segmentation, extraction and tracking of relevant static and dynamic features related to manual and nonmanual gestures from different images in sequence. In this paper, we studied the efficiency, scalability, and computation time of three cascaded architectures of convolutional …

Segmentation Of Diatoms Using Edge Detection And Deep Learning, Hüseyi̇n Gündüz, Cüneyd Nadi̇r Solak, Serkan Günal

Turkish Journal of Electrical Engineering and Computer Sciences

Diatoms are photosynthesizing algae found in almost every aquatic environment. Detecting the number and diversity of diatoms is very important to analyze water quality appropriately. Accurate segmentation of diatoms is therefore crucial for this detection process. In this study, a new and effective model for the automatic segmentation of diatoms based on image processing and deep learning algorithms is proposed. In the proposed model, edge segments of a given image containing diatoms and nondiatom particles are first obtained. These edge segments are then combined, resulting in closed contours representing diatom candidates. In the final step, the diatom candidates are classified …

Image Restoration Under Adverse Illumination For Various Applications, Lan Fu

Theses and Dissertations

Many images are captured in sub-optimal environment, resulting in various kinds of degradations, such as noise, blur, and shadow. Adverse illumination is one of the most important factors resulting in image degradation with color and illumination distortion or even unidentified image content. Degradation caused by the adverse illumination makes the images suffer from worse visual quality, which might also lead to negative effects on high-level perception tasks, e.g., object detection.

Image restoration under adverse illumination is an effective way to remove such kind of degradations to obtain visual pleasing images. Existing state-of-the-art deep neural networks (DNNs) based image restoration …

Analyzing The Influence Of Smart-Device Visual Features, Viewing Distance And Content Factors On Video Streaming Qoe, Alex Frank Mongi

Tanzania Journal of Engineering and Technology (TJET)

Quality of experience (QoE) over wireless networks has attracted attention from industry and academia due to an increase in video streaming applications. Several researchers have attempted to understand the factors affecting QoE and design appropriate quality control strategies. Normally, video streaming is initiated by a user who accesses video content over a network using a smart device that may be held at various viewing distances. Each aforementioned factor has the potential to affect QoE. However, several studies explore the behavior of wireless networks on video streaming QoE. To understand the effects of other factors on QoE, this paper investigates the …

Advancing Towards A More Complete Sign Language Detection Application, Shane Angel

Undergraduate University Honors Capstones

The goal of this capstone is to improve the experiences of Deaf and Hard of Hearing individuals who use teleconferencing tools through the use of sign language detection software. Popular teleconferencing applications such as Zoom and Google Meet contain features that can automatically spotlight users when they are speaking, but there is currently no equivalent feature for those who used signed languages to communicate on these platforms. Such a feature would need to utilize a sign language detection program to spotlight individuals, but this technology is early in development and is not currently available for large-scale implementation. This capstone strives …

A New Effective Denoising Filter For High Density Impulse Noise Reduction, Iman Elawady, Caner Özcan

Turkish Journal of Electrical Engineering and Computer Sciences

Today, thanks to the rapid development of technology, the importance of digital images is increasing. However, sensor errors that may occur during the acquisition, interruptions in the transmission of images and errors in storage cause noise that degrades data quality. Salt and pepper noise, a common impulse noise, is one of the most well-known types of noise in digital images. This noise negatively affects the detailed analysis of the image. It is very important that pixels affected by noise are restored without loss of image fine details, especially at high level of noise density. Although many filtering algorithms have been …

Two Person Interaction Recognition Based On A Dual-Coded Modified Metacognitive (Dcmmc) Extreme Learning Machine, Saman Nikzad, Afshin Ebrahimi

Turkish Journal of Electrical Engineering and Computer Sciences

Human action recognition has been an active research area for over three decades. However, state-of-the-art proposed algorithms are still far from developing error-free and fully-generalized systems to perform accurate interaction recognition. This work proposes a new method for two-person interaction recognition from videos, based on well-known cognitive theories. The main idea is to perform classification based on a theory of cognition known as dual coding theory. The theory states that human brain processes and represents two types of information to learn/classify data named analogue and symbolic codes, i.e. (verbal as analogue and visual as symbolic). To implement such a theory …

Characterizing And Predicting Human Visual Perception Of Unmanned Aerial Vehicle Gestures, Paul Fletcher

School of Computing: Dissertations, Theses, and Student Research

Unmanned Aerial Vehicles (UAVs) are being used in public domains and hazardous environments where effective communication strategies are critical. UAV gesture techniques have been shown to communicate meaning to human observers and may be ideal in contexts that require lightweight systems such as unmanned aerial flight, however, this work may be limited to an idealized range of viewer perspectives. As gesture is a visual communication technique it is necessary to consider how the perception of a robot gesture may suffer from obfuscation or self-occlusion from some viewpoints. This thesis presents the results of three online user-studies that examine participants’ ability …

Investigating Collaboration In Software Reverse Engineering, Allison M. Wong

Theses and Dissertations

Reverse engineering (RE) is a rigorous process of exploration and analysis to support software design recovery and exploit development. The process is often conducted in teams to divide the workload and take full advantage of engineers' individual expertise and strengths. Collaboration in RE requires versatile and reliable tools that can match the environment's unpredictable and fluid nature. While studies on collaborative software development have indicated common best practices and implementations, similar standards have not been explored in reverse engineering. This research conducts semi-structured interviews with reverse engineering experts to understand their needs and solutions while working in a team. The …

Design Demand Trend Acquisition Method Based On Short Text Mining Of User Comments In Shopping Websites, Zhiyong Xiong, Zhaoxiong Yan, Huanan Yao, Shangsong Liang

Machine Learning Faculty Publications

In order to facilitate designers to explore the market demand trend of laptops and to establish a better “network users-market feedback mechanism”, we propose a design and research method of a short text mining tool based on the K-means clustering algorithm and Kano mode. An improved short text clustering algorithm is used to extract the design elements of laptops. Based on the traditional questionnaire, we extract the user’s attention factors, score the emotional tendency, and analyze the user’s needs based on the Kano model. Then, we select 10 laptops, process them by the improved algorithm, cluster the evaluation words and …

A Multidisciplinary Collaboration Between Graphic Design And Physics Classes Responding To Covid-19, Szilvia Kadas, Eric M. Edlund

The SUNY Journal of the Scholarship of Engagement: JoSE

Students from graphic design and physics classes at SUNY Cortland collaborated during the spring semester of 2020 on a multidisciplinary project related to the COVID-19 pandemic. In these collaborations, the students’ individual contributions were part of a larger project that required a diverse skill set, through which students learned how different skills can complement their own disciplines. The graphic design and physics instructors applied a project-based learning philosophy applying the Common Problem Pedagogy (CPP) framework to construct student-teams composed of both disciplines. This project explored how coordinated social actions can allow the public to exercise control in uncertain times. Students …

คุณสมบัติและทักษะที่จำเป็นสำหรับสกรัมมาสเตอร์ในความคาดหวังของผู้ร่วมทีมสกรัม, อริณชาดา อัศวรัตนมนตรี

Chulalongkorn University Theses and Dissertations (Chula ETD)

วิธีการทำงานแบบสกรัม (Scrum Methodology) เป็นหนึ่งในวิธีการพัฒนาซอฟต์แวร์แบบอไจล์ (Agile Software Development) ที่ได้รับความนิยมในปัจจุบัน ทีมพัฒนาซอฟต์แวร์แบบสกรัม เป็นทีมที่สามารถจัดการตนเองได้ กล่าวคือ สมาชิกของทีมรู้บทบาทหน้าที่ของตนเองและทํางานแบบ “ข้ามฟังก์ชันงาน” (Cross-Functional) ไม่มีการกำหนดหน้าที่ หรือตําแหน่งงานภายในทีมกันอย่างชัดเจนตายตัว มีเพียงแค่การกําหนดบทบาทหลักๆ ไว้ 3 บทบาทเท่านั้น คือ ทีมนักพัฒนา (Development Team) สกรัมมาสเตอร์ (Scrum Master) และเจ้าของผลิตภัณฑ์ (Product Owner) ส่งผลให้ผู้ร่วมทีมสกรัมต้องทํางานที่หลากหลาย ทั้งที่ตนเองถนัดและไม่ถนัด ดังนั้นสกรัมมาสเตอร์จําเป็นต้องมีทักษะที่เพียงพอ เพื่อช่วยให้ผู้ร่วมทีมสกรัมสามารถทํางานตามวัตถุประสงค์ที่วางไว้ร่วมกันได้ งานวิจัยนี้เป็นงานวิจัยเชิงสำรวจ (Survey Research) ใช้การเก็บข้อมูลจากการตอบแบบสอบถามออนไลน์และการใช้แบบสอบถามออนไลน์เป็นเครื่องมือในการเก็บข้อมูล จากบริษัทที่ใช้วิธีการทำงานแบบสกรัมพัฒนาซอฟต์แวร์ในไทย ใช้เวลาในการเก็บข้อมูล 3 เดือน ผลการวิจัย พบว่าทักษะที่จำเป็นสำหรับสกรัมมาสเตอร์จากมุมมองผู้ร่วมทีมสกรัมของบริษัทพัฒนาซอฟต์แวร์ในไทย (1) สกรัมมาสเตอร์มองว่า วิธีการทำงานแบบสกรัม (Scrum Process) สำคัญที่สุดสำหรับทักษะด้านเทคนิค เช่นเดียวกับมุมมองของเจ้าของผลิตภัณฑ์ และทักษะการทำความเข้าใจ (Understanding Skills) สำคัญที่สุดสำหรับจรณทักษะ (2) เจ้าของผลิตภัณฑ์มองว่า ความมุ่งมั่น (Commitment, Responsibility) สำคัญที่สุดสำหรับจรณทักษะ (3) ทีมนักพัฒนามองว่า เครื่องมือรวบรวมโค้ด (code) ที่ได้รับการพัฒนาจากสมาชิกเเต่ละคนในทีมให้เป็นชิ้นเดียว (Continuous Integration Tools) สำคัญที่สุดสำหรับทักษะด้านเทคนิค และการทำงานเป็นทีม (Teamwork) สำคัญที่สุดสำหรับจรณทักษะ โดยรวมแล้วผู้ร่วมทีมสกรัมให้ความสำคัญกับทักษะด้านเทคนิค และจรณทักษะไม่แตกต่างกัน งานวิจัยนี้สามารถนำไปใช้กับการพิจารณาคุณสมบัติของสกรัมมาสเตอร์

Explicating Consumer Adoption Of Wearable Technologies: A Case Of Smartwatches From The Asean Perspective, Veerisa Chotiyaputta, Donghee Shin

All Works

This research aims to determine the key antecedent factors in consumers' adoption of and their intention to recommend smartwatch wearable technology. The proposed research model combines the current technology acceptance and innovation diffusion theories with perceived aesthetic and perceived privacy risk to explain individuals' smartwatch adoption and subsequent recommendation to other people. Based on a sample of 299 completed individual online surveys, the research employed partial least squares (a variance-based analysis method) for the model and hypotheses testing. The results showed some similarities as well as differences from the previous literature. The study found that performance expectancy, habit, and perceived …

On The Use Of Allen’S Interval Algebra In The Coordination Of Resource Consumption By Transactional Business Processes, Zakaria Maamar, Fadwa Yahya, Lassaad Ben Ammar

All Works

This paper presents an approach to coordinate the consumption of resources by transactional business processes. Resources are associated with consumption properties known as unlimited, limited, limited-but-extensible, shareable, and non-shareable restricting their availabilities at consumption-time. And, processes are associated with transactional properties known as pivot, retriable, and compensatable restricting their execution outcomes in term of either success or failure. To consider the intrinsic characteristics of both consumption properties and transactional properties when coordinating resource consumption by processes, the approach adopts Allen’s interval algebra through different time-interval relations like before, overlaps, and during to set up the coordination, which should lead to …

Toward Video-Conferencing Tools For Hands-On Activities In Online Teaching, Audrey Labrie, Terrance Mok, Anthony Tang, Michelle Lui, Lora Oehlberg, Lev Poretski

Research Collection School Of Computing and Information Systems

Many instructors in computing and HCI disciplines use hands-on activities for teaching and training new skills. Beyond simply teaching hands-on skills like sketching and programming, instructors also use these activities so students can acquire tacit skills. Yet, current video-conferencing technologies may not effectively support hands-on activities in online teaching contexts. To develop an understanding of the inadequacies of current video-conferencing technologies for hands-on activities, we conducted 15 interviews with university-level instructors who had quickly pivoted their use of hands-on activities to an online context during the early part of the COVID-19 pandemic. Based on our analysis, we uncovered four pedagogical …

Research On Accurate Gesture Recognition Algorithm In Complex Environment Based On Machine Vision, Xu Sheng, Wenyu Feng, Zhicheng Liu, Xintao Tu, Minrui Fei, Kun Zhang

Journal of System Simulation

Abstract: To address the issue of cross infection caused by elevator public buttons during COVID-19, a software algorithm based on machine vision for non-contact control of public buttons by gesture recognition is designed. In order to improve the accuracy of gesture recognition, an improved YOLOv4 algorithm is proposed. A Ghost module is designed based on attention mechanism, and the ResBlock module in YOLOv4 is improved to Ghost module. The experimental results show that, in the task of gesture recognition, the detection speed is improved by 14% and the detection accuracy is improved by 0.1% compared with the original model. The …

Self-Regulation For Semantic Segmentation, Dong Zhang, Hanwang Zhang, Jinhui Tang, Xian-Sheng Hua, Qianru Sun

Research Collection School Of Computing and Information Systems

In this paper, we seek reasons for the two major failure cases in Semantic Segmentation (SS): 1) missing small objects or minor object parts, and 2) mislabeling minor parts of large objects as wrong classes. We have an interesting finding that Failure-1 is due to the underuse of detailed features and Failure-2 is due to the underuse of visual contexts. To help the model learn a better trade-off, we introduce several Self-Regulation (SR) losses for training SS neural networks. By “self”, we mean that the losses are from the model per se without using any additional data or supervision. By …

Uncovering Patterns In Reviewers' Feedback To Scene Description Authors, Rosiana Natalie, Jolene Kar Inn Loh, Huei Suen Tan, Joshua Shi-Hao Tseng, Hernisa Kacorri, Kotaro Hara

Research Collection School Of Computing and Information Systems

Audio descriptions (ADs) can increase access to videos for blind people. Researchers have explored different mechanisms for generating ADs, with some of the most recent studies involving paid novices; to improve the quality of their ADs, novices receive feedback from reviewers. However, reviewer feedback is not instantaneous. To explore the potential for real-time feedback through automation, in this paper, we analyze 1,120 comments that 40 sighted novices received from a sighted or a blind reviewer. We find that feedback patterns tend to fall under four themes: (i) Quality; commenting on different AD quality variables, (ii) Speech Act; the utterance or …

Rotten With Prediction, Serena Raquel Hicks

UNLV Theses, Dissertations, Professional Papers, and Capstones

This project focuses on the relationship between religion and technology as it is portrayed in Science Fiction (SF). This thesis explores the SF genre rhetorically by examining the 2002 movie Minority Report (MR), which signaled the importance of surveillance and the need to predict future crimes following 9/11. The events of 9/11 played a significant role in post 9/11 SF films, which reflect and critique our communal and cultural values. 9/11 created a new relationship between the U.S justice system, predictive technologies (PTs), and data gathering. Through the Bush Doctrine of “preemptive action,” the U.S government attempted to use Dataism, …

Uncertainty-Aware Visualization In Medical Imaging - A Survey, Christina Gillmann, Dorothee Saur, Thomas Wischgoll, Gerik Scheuermann

Computer Science and Engineering Faculty Publications

Medical imaging (image acquisition, image transformation, and image visualization) is a standard tool for clinicians in order to make diagnoses, plan surgeries, or educate students. Each of these steps is affected by uncertainty, which can highly influence the decision-making process of clinicians. Visualization can help in understanding and communicating these uncertainties. In this manuscript, we aim to summarize the current state-of-the-art in uncertainty-aware visualization in medical imaging. Our report is based on the steps involved in medical imaging as well as its applications. Requirements are formulated to examine the considered approaches. In addition, this manuscript shows which approaches can be …

Pedestrian Attribute Recognition Using Two-Branch Trainable Gabor Wavelets Network, Imran N. Junejo

All Works

Keeping an eye on pedestrians as they navigate through a scene, surveillance cameras are everywhere. With this context, our paper addresses the problem of pedestrian attribute recognition (PAR). This problem entails recognizing attributes such as age-group, clothing style, accessories, footwear style etc. This multi-label problem is extremely challenging even for human observers and has rightly garnered attention from the computer vision community. Towards a solution to this problem, in this paper, we adopt trainable Gabor wavelets (TGW) layers and cascade them with a convolution neural network (CNN). Whereas other researchers are using fixed Gabor filters with the CNN, the proposed …

Social Media User Relationship Framework (Smurf), Anne David, Sarah Morris, Gareth Appleby-Thomas

Journal of Digital Forensics, Security and Law

The use of social media has spread through many aspects of society, allowing millions of individuals, corporate as well as government entities to leverage the opportunities it affords. These opportunities often end up being exploited by a small percentage of the user community who use it for objectionable or unlawful activities; for example, trolling, cyber bullying, grooming, luring. In some cases, these unlawful activities result in investigations where swift retrieval of critical evidence required in order to save a life.

This paper presents a proof of concept (PoC) framework for social media user attribution. The framework aims to provide digital …

A Novel Hybrid Decision-Based Filter And Universal Edge-Based Logical Smoothingadd-On To Remove Impulsive Noise, Rajanbir Singh Ghumaan, Prateek Jeet Singh Sohi, Nikhil Sharma, Bharat Garg

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a novel hybrid filter along with a universal extension to remove salt and pepper noise even at a very high noise density. The proposed filter initially specifies a threshold and then denoises the image using a combination of linear, nonlinear, and probabilistic techniques. Furthermore, to improve the quality, a universal add-on is presented which uses edge detection and smoothening techniques to brush out fine details from the restored image. To evaluate the efficacy, the proposed and existing filtering techniques are implemented in MATLAB and simulated with benchmark images. The simulation results show that the proposed filter is …

Efficient Hybrid Passive Method For The Detection And Localization Of Copy-Moveand Spliced Images, Navneet Kaur, Neeru Jindal, Kulbir Singh

Turkish Journal of Electrical Engineering and Computer Sciences

Digital passive image forgery methods are extensively used to verify the authenticity and integrity of images.Splicing and copy-move are the most common types of passive digital image forgeries. Several approaches have beenproposed to detect these forgeries separately, but very few approaches are available that can detect them simultaneously.However, a more e?icient method is still in demand to meet the day-to-day challenges to detect these forgeries at thesame time. So, a passive hybrid approach based on discrete fractional cosine transform (DFrCT) and local binarypattern (LBP) is proposed to detect copy-move and splicing forgeries simultaneously. The extra parameter i.e. fractionalparameter of DFrCT …

An Evolutionary-Based Image Classification Approach Through Facial Attributes, Seli̇m Yilmaz, Cemi̇l Zalluhoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

With the recent developments in technology, there has been a significant increase in the studies on analysisof human faces. Through automatic analysis of faces, it is possible to know the gender, emotional state, and even theidentity of people from an image. Of them, identity or face recognition has became the most important task whichhas been studied for a long time now as it is crucial to take measurements for public security, credit card verification,criminal identification, and the like. In this study, we have proposed an evolutionary-based framework that relies ongenetic programming algorithm to evolve a binary- and multilabel image classifier …

Learning Multiview Deep Features From Skeletal Sign Language Videos Forrecognition, Ashraf Ali Shaik, Venkata Durga Prasad Mareedu, Venkata Vijaya Kishore Polurie

Turkish Journal of Electrical Engineering and Computer Sciences

The most challenging objective in machine translation of sign language has been the machine?s inability tolearn interoccluding finger movements during an action process. This work addresses the problem of teaching a deeplearning model to recognize differently oriented skeletal data. The multi-view 2D skeletal sign language video data isobtained using 3D motion-captured system. A total of 9 signer views were used for training the proposed network andthe 6 for testing and validation. In order to obtain multi-view deep features for recognition, we proposed an end-to-endtrainable multistream convolutional neural network (CNN) with late feature fusion. The fused multiview features arethen inputted to …

Turkish Sign Language Recognition Based On Multistream Data Fusion, Cemi̇l Gündüz, Hüseyi̇n Polat

Turkish Journal of Electrical Engineering and Computer Sciences

Sign languages are nonverbal, visual languages that hearing- or speech-impaired people use for communication.Aside from hands, other communication channels such as body posture and facial expressions are also valuable insign languages. As a result of the fact that the gestures in sign languages vary across countries, the significance ofcommunication channels in each sign language also differs. In this study, representing the communication channels usedin Turkish sign language, a total of 8 different data streams-4 RGB, 3 pose, 1 optical flow-were analyzed. Inception3D was used for RGB and optical flow; and LSTM-RNN was used for pose data streams. Experiments were conductedby …

Coordination, Adaptation, And Complexity In Decision Fusion, Weiqiang Dong

Dissertations

A parallel decentralized binary decision fusion architecture employs a bank of local detectors (LDs) that access a commonly-observed phenomenon. The system makes a binary decision about the phenomenon, accepting one of two hypotheses (H0 (“absent”) or H1 (“present”)). The k 1 LD uses a local decision rule to compress its local observations yk into a binary local decision uk; uk = 0 if the k 1 LD accepts H0 and uk = 1 if it accepts H1. The k 1 LD sends its decision uk over a noiseless dedicated channel to a Data Fusion Center (DFC). The DFC combines the …

Research And Application Of A Lightweight Real-Time Human Posture Detection Model, Hongkun Zhu, Jiawei Yin, Wenyu Feng, Hua Liang, Minrui Fei, Kun Zhang

Journal of System Simulation

Abstract: The traditional OpenPose model has good accuracy but slow speed in human posture detection. In order to accelerate the detection speed and reduce the model on condition of the detection precision, based on the traditional OpenPose model, the residual network with second-order term fusion is used to extract the low-level features, the weights of the trained model are pruned by the L1 norm weight, and an improved OpenPose model is proposed. Experiments show that when the detection accuracy is approximately equal to original model, the model size reduces to about 8%, the parameters reduces by nearly 83%, and the …

Fast 3d Medical Image Registration Based On Geometric Feature Invariants, Juping Gu, Tianyu Cheng, Jianping Wang, Hua Liang, Fengshen Zhao, Jiang Ling

Journal of System Simulation

Abstract: Aiming at the of large amount of computational data and low registration efficiency in 3D cranial medical image registration, a fast registration method based on geometric feature space constraints is proposed. The algorithm extracts three-dimensional contour point clusters, and proposes a feature construction method based on the optimal fitting ring of point clusters. The feature rings and the centroids of each layer are used as feature quantities, and the fast registration is completed by using Iterative Closest Point (ICP) method. The experimental results show that the method has less computation amount, high satisfactory registration accuracy and much faster registration …