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.
Yolo Versions Architecture: Review
Artificial Neural Networks
Deep Learning
YOLO
YOLO Version
Publication Date
Sat Oct 01 2022
Journal Name
Alexandria Engineering Journal
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Wed Apr 01 2020
Journal Name
Biochem. Cell. Arch.
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Sat Dec 01 2018
Journal Name
Swarm And Evolutionary Computation
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Publication Date
Mon Jun 26 2023
Journal Name
Asia-pacific Journal Of Chemical Engineering
Sustainable environment through using porous materials: A review on wastewater treatment
Abstract<p>Porous materials play an important role in creating a sustainable environment by improving wastewater treatment's efficacy. Porous materials, including adsorbents or ion exchangers, catalysts, metal–organic frameworks, composites, carbon materials, and membranes, have widespread applications in treating wastewater and air pollution. This review examines recent developments in porous materials, focusing on their effectiveness for different wastewater pollutants. Specifically, they can treat a wide range of water contaminants, and many remove over 95% of targeted contaminants. Recent advancements include a wider range of adsorption options, heterogeneous catalysis, a new UV/H<sub>2</sub>O<j></j></p>
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Publication Date
Thu Dec 05 2013
Journal Name
Robotica
Modeling, stability and walking pattern generators of biped robots: a review
SUMMARY<p>Biped robots have gained much attention for decades. A variety of researches have been conducted to make them able to assist or even substitute for humans in performing special tasks. In addition, studying biped robots is important in order to understand human locomotion and to develop and improve control strategies for prosthetic and orthotic limbs. This paper discusses the main challenges encountered in the design of biped robots, such as modeling, stability and their walking patterns. The subject is difficult to deal with because the biped mechanism intervenes with mechanics, control, electronics and artificial intelligence. In this paper, we collect and introduce a systematic discussion of modelin</p>
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Publication Date
Fri May 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
A review of ultra-high temperature materials for thermal protection system
Abstract<p>Ultra-High Temperature Materials (UHTMs) are at the base of entire aerospace industry; these high stable materials at temperatures exceeding 1600 °C are used to manage the heat shielding to protect vehicles and probes during the hypersonic flight through reentry trajectory against aerodynamic heating and reducing plasma surface interaction. Those materials are also recognized as Thermal Protection System Materials (TPSMs). The structural materials used during the high-temperature oxidizing environment are mainly limited to SiC, oxide ceramics, and composites. In addition to that, silicon-based ceramic has a maximum-use at 1700 °C approximately; as it is an active oxidation process o</p>
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Publication Date
Sat Jan 01 2022
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Materials Today: Proceedings
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Mon Jul 01 2024
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World Neurosurgery
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Tue Jan 01 2019
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Plant Archives
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Tue Feb 01 2022
Journal Name
Journal Of Engineering
Self-Repairing Technique Based on Microcapsules for Cementitious Composites- A Review
Self-repairing
Micro-capsules
Repairing factors
Investigative methodologies
Nondestructive methods
Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab
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