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Optimizing Application of UAV-Based SfM Photogrammetric 3D Mapping in Urban Areas
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In recent years, the extensive need for high-quality acquisition platforms for various 3D mapping applications has rapidly increased, especially in sensor performance, portability, and low cost. Image-based UAV sensors have overwhelming merits over alternative solutions for their high timeline and resilience data acquisition systems and the high-resolution spatial data they can provide through extensive Computer Vision (CV) data processing approaches. However, applying this technique, including the appropriate selection of flight mission and image acquisition parameters, ground settings and targeting, and Structure from Motion- Multi-View Stereo (SfM-MVS) post-processing, must be optimized to the type of study site and feature characteristics. This research focuses on optimizing the application of UAV-SfM photogrammetry in an urban area on the east bank of the Tigris River in the north region of Iraq following optimized data capturing plan and SfM-MVS photogrammetric workflow. The research presented the practical application of optimized flight planning, data acquisition, image processing, accuracy analysis, and evaluation based on ground truth targets designed for the proposed optimal routine. This includes investigating the influence of the number and distribution of GCPs, flying heights, and processing parameters on the quality of the produced 3D data. The research showed the potential of low-budget and affordable UAV devices to deliver robust 3D products in a relatively short period by demonstrating the value of UAV-based image techniques when contributed to CV algorithms. The results showed powerful outcomes with validation errors reaching a centimeter-level from 100 m flying height when applying the optimized flight plan settings and the appropriate selection of the number and distribution of GCPs. The study established a streamlined UAV mapping procedure, demonstrated the viability of UAV use for 3D mapping applications, offered suggestions for enhancing future applications, and offered clues as to whether or not UAVs could serve as a viable alternative to conventional ground-based surveying techniques in accurate applications.

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Publication Date
Fri Dec 29 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Smartphone -Based Model for Human Activity Recognition
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Activity recognition (AR) is a new interesting and challenging research area with many applications (e.g. healthcare, security, and event detection). Basically, activity recognition (e.g. identifying user’s physical activity) is more likely to be considered as a classification problem. In this paper, a combination of 7 classification methods is employed and experimented on accelerometer data collected via smartphones, and compared for best performance. The dataset is collected from 59 individuals who performed 6 different activities (i.e. walk, jog, sit, stand, upstairs, and downstairs). The total number of dataset instances is 5418 with 46 labeled features. The results show that the proposed method of ensemble boost-based classif

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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Publication Date
Sat Oct 01 2022
Journal Name
Therapeutic Delivery
Particles-based Medicated Wound Dressings: A Comprehensive Review
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Publication Date
Thu Aug 01 2019
Journal Name
2019 2nd International Conference On Engineering Technology And Its Applications (iiceta)
Human Gait Identification System Based on Average Silhouette
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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Improve topic modeling algorithms based on Twitter hashtags
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Abstract<p>Today with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned</p> ... Show More
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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Electronic Security And Digital Forensics
LSB based audio steganography preserving minimum sample SNR
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Publication Date
Wed Mar 08 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Genetic –Based Face Retrieval Using Statistical Features
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Content-based image retrieval has been keenly developed in numerous fields. This provides more active management and retrieval of images than the keyword-based method. So the content based image retrieval becomes one of the liveliest researches in the past few years. In a given set of objects, the retrieval of information suggests solutions to search for those in response to a particular description. The set of objects which can be considered are documents, images, videos, or sounds. This paper proposes a method to retrieve a multi-view face from a large face database according to color and texture attributes. Some of the features used for retrieval are color attributes such as the mean, the variance, and the color image's bitmap. In add

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Publication Date
Tue Feb 01 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Computer-based plagiarism detection techniques: A comparative study
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Plagiarism is becoming more of a problem in academics. It’s made worse by the ease with which a wide range of resources can be found on the internet, as well as the ease with which they can be copied and pasted. It is academic theft since the perpetrator has ”taken” and presented the work of others as his or her own. Manual detection of plagiarism by a human being is difficult, imprecise, and time-consuming because it is difficult for anyone to compare their work to current data. Plagiarism is a big problem in higher education, and it can happen on any topic. Plagiarism detection has been studied in many scientific articles, and methods for recognition have been created utilizing the Plagiarism analysis, Authorship identification, and

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Publication Date
Mon Apr 15 2019
Journal Name
Proceedings Of The International Conference On Information And Communication Technology
Hybrid LDPC-STBC communications system based on chaos
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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Al-nahrain University Science
Breaking Knapsack Cipher Using Population Based Incremental Learning
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