Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing items in images. This article, will be focusing on comparing the main differences among the YOLO version's Architecture, and will discuss its evolution from YOLO to YOLOv8, its network architecture, new features, and applications. And starts by looking at the basic ideas and design of the first YOLO model, which laid the groundwork for the following improvements in the YOLO family. In additionally, this article will provide a step-by-step guide on how to use the YOLO version architecture, Understanding the primary drivers, feature development, constraints, and even relationships for the versions is crucial as the YOLO versions advance. Researchers interested in object detection, especially beginning researchers, would find this paper useful and enlightening.
With the high usage of computers and networks in the current time, the amount of security threats is increased. The study of intrusion detection systems (IDS) has received much attention throughout the computer science field. The main objective of this study is to examine the existing literature on various approaches for Intrusion Detection. This paper presents an overview of different intrusion detection systems and a detailed analysis of multiple techniques for these systems, including their advantages and disadvantages. These techniques include artificial neural networks, bio-inspired computing, evolutionary techniques, machine learning, and pattern recognition.
This research aims to realize one of the pillars of Saudi vision (2030) through searching for new sources full of material folklore that had not previously been studied, so this study will study folk motifs engraved on the doors and windows in the Bani Amru Center in the Al-Namas governorate that is situated in the Asir region , in particular the tribe (Bani Rafe), before being disappeared due to the abandonment of the old architecture by the people of the region and their fascination with modern architecture, therefore I must as one of the people of the region document and preserve that through studying, analyzing, classifying it, then inspiring typed paintings using a new technical typing that have not yet been used in the Kingd
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The current research is interested in studying the symbol, due to its significant role in the architecture and arts in the holy shrines regardless of their architecture and artistic patterns, through which the symbolic and philosophical connotations insides the holy shrines are revealed. Due to the importance of the topic of the symbol, Almighty God remarked in the holy Quran (He said, "My Lord, make for me a sign." He Said, "Your sign is that you will not [be able to] speak to the people for three days except by gesture. And remember your Lord much and exalt [Him with praise] in the evening and the morning.") (Surat Al-Imran, verse 41). The research consists of two dimensions dealing with symbol and symbolism in its linguistic an
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Cloud-based Electronic Health Records (EHRs) have seen a substantial increase in usage in recent years, especially for remote patient monitoring. Researchers are interested in investigating the use of Healthcare 4.0 in smart cities. This involves using Internet of Things (IoT) devices and cloud computing to remotely access medical processes. Healthcare 4.0 focuses on the systematic gathering, merging, transmission, sharing, and retention of medical information at regular intervals. Protecting the confidential and private information of patients presents several challenges in terms of thwarting illegal intrusion by hackers. Therefore, it is essential to prioritize the protection of patient medical data that is stored, accessed, and shared on
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The concept of aesthetics is one of the postmodern propositions, and it is one of the branches of philosophy that examines beauty, its standards and theories, and it is a holistic concept that includes several concepts, including the beautiful, the ugly, and the sublime.
The concept of aesthetics dealt with several studies in general (and in the field of architecture in particular), and the problem of aesthetics is in the blurring of the relationship between aesthetics and architectural criticism, based on the research hypothesis which states that there is a relationship between aesthetics and architectural criticism. The importance of the research in accommodating aesthetic standards and bases of evaluation that increases the possi
Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)
In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare
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Hellenistic architecture represents an important example of the reflection of ancient Greek architecture in the art of oriental architecture in the countries of the ancient world, including those states spread across North Africa that were under the authority of the Ptolemies and who were able to transmit those artistic values and traditions of Greek architecture to those regions. The current research deals with a detailed study of those important transformations of civil and religious architecture, as well as the most important features of that architecture through the constituents of location and geographical location.
Optical Mark Recognition (OMR) is the technology of electronically extracting intended data from marked fields, such as squareand bubbles fields, on printed forms. OMR technology is particularly useful for applications in which large numbers of hand-filled forms need to be processed quickly and with a great degree of accuracy. The technique is particularly popular with schools and universities for the reading in of multiple choice exam papers. This paper proposed OMRbased on Modify Multi-Connect Architecture (MMCA) associative memory, its work in two phases: training phase and recognition phase. The proposed method was also able to detect more than one or no selected choice. Among 800 test samples with 8 types of grid answer sheets and tota
... Show MoreThis research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.