Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. 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 andclassification 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, newfeatures, and applications. Itstarts 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
Low back pain a major causes of morbidity throughout the world and it is a most debilitating condition ,and can lead to decreased physical function ,compromised quality of life, and psychological distress. Obesity is nowadays a pandemic condition. Obese subjects are commonly characterized by musculoskeletal disorders and particularly by non-specific LBP. However, the relationship between obesity and LBP remain to date unsupported by objective measurements of mechanical behavior of spine and it is morphology in obese subjects. Key words: obesity, low back pain,
Background: Significant advancements have been observed in the additive manufacturing (AM) technology industry in recent decades. Due to the inherent variations among each AM manufacturing technique, new areas of investigation continually arise and require consideration. Additionally, the novel applications of additive manufacturing present new difficulties and possibilities for targeted focus. The aim of this manuscript is to conduct a comprehensive literature review that describes the various processing methods, precision levels, types of materials utilized, and potential applications of 3D printing technology in the field of dentistry. Data: An online search was conducted on databases including Research Gate, Google Scholar, and
... Show MoreObjectives: To review the failure rates of molar tubes and the effect of molar tube base design, adhesive type, and bonding technique on the failure rates of molar tubes. Data: The revolution of molar bonding greatly impacted fixed orthodontic appliance treatment by reducing chair-side time and improving patient comfort. Even with the many advantages of molar bonding, clinicians sometimes hesitate to use molar tubes due to their failure rates. Sources: Internet sources, such as Pubmed and Google Scholar. Study selection: studies testing the bond failure rate of molar tubes. Conclusions: The failure rate of the molar tubes can be reduced and the bond strength of the molar tubes can be improved by changing the design of the molar tube base
... Show MoreIn this research, we highlight the most important research related to the mixed ligand complexes of the drug trimethoprim (TMP), and for the past 7 years where this drug has been used as a chelating ligand and gives stability to the complexes with ions of metal elements where these complexes, prepared and diagnosed, and for some research the bacterial activity was studied against different types of bacteria
Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing
... Show MoreBackground: The transcriptional control of various cell types, especially in the development or functioning of immune system cells involved in either promoting or inhibiting the immune response against cancer, is significantly influenced by DNA or RNA methylation. Multifaceted interconnections exist between immunological or cancer cell populations in the tumor's microenvironment (TME). TME alters the fluctuating DNA (as well as RNA) methylation sequences in these immunological cells to change their development into pro- or anti-cancer cell categories (such as T cells, which are regulatory, for instance). Objective: This review highlights the impact of DNA and RNA methylation on myeloid and lymphoid cells, unraveling their intricate
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