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.
The demand for electronic -passport photo ( frontal facial) images has grown rapidly. It now extends to Electronic Government (E-Gov) applications such as social benefits driver's license, e-passport, and e-visa . With the COVID 19 (coronavirus disease ), facial (formal) images are becoming more widely used and spreading quickly, and are being used to verify an individual's identity, but unfortunately that comes with insignificant details of constant background which leads to huge byte consumption that affects storage space and transmission, where the optimal solution that aims to curtail data size using compression techniques that based on exploiting image redundancy(s) efficiently.
Image Fusion is being used to gather important data from such an input image array and to place it in a single output picture to make it much more meaningful & usable than either of the input images. Image fusion boosts the quality and application of data. The accuracy of the image that has fused depending on the application. It is widely used in smart robotics, audio camera fusion, photonics, system control and output, construction and inspection of electronic circuits, complex computer, software diagnostics, also smart line assembling robots. In this paper provides a literature review of different image fusion techniques in the spatial domain and frequency domain, such as averaging, min-max, block substitution, Intensity-Hue-Saturation(IH
... Show MoreFor the duration of the last few many years many improvement in computer technology, software program programming and application production had been followed with the aid of diverse engineering disciplines. Those trends are on the whole focusing on synthetic intelligence strategies. Therefore, a number of definitions are supplied, which recognition at the concept of artificial intelligence from exclusive viewpoints. This paper shows current applications of artificial intelligence (AI) that facilitate cost management in civil engineering tasks. An evaluation of the artificial intelligence in its precise partial branches is supplied. These branches or strategies contributed to the creation of a sizable group of fashions s
... Show MoreThe COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system
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In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne
... Show MoreTook apple branches Genuine and Architecture tissue cultured in vitro 3 cm long and planted in the middle of food MS that contains different concentrations of inorganic salts and of Mntmat free growth and incubated Transplanter to study their effect on rooting Aalavra
Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio
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Buildings begin to deteriorate gradually over time due to several factors, including environmental influences, improper use of the building, and neglected repairs for damages during the building's life span. Effective maintenance practices can minimize operational costs, extend the life of building systems and components, improve energy efficiency, and maintain property value. This paper aims to review articles related to building maintenance to identify factors affecting maintenance practices. After conducting the review, the result was that there were 33 factors affecting building maintenance categorized into six groups: management-related factors, manpower-related factors, technical-related factors, financial-
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Pulsatile drug delivery systems (PDDS) are developed to deliver drug according to circadian behavior of diseases. They deliver the drug at the right time, action and in the right amount, which provides more benefit than conventional dosages and increased patient compliance. The drug is released rapidly and completely as a pulse after a lag time. These systems are beneficial for drugs with chrono-pharmacological behavior, where nighttime dosing is required and for the drugs having a high first-pass effect and having specific site of absorption in the gastrointestinal tract. This article covers methods and marketed technologies that have been developed to achieve pulsatile delivery. Diseases wherein PDDS are promising include asthma, peptic u
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