AI-based object detection latest trends in remote sensing, multimedia and agriculture applications

Nawaz, Saqib Ali; Li, Jingbing; Bhatti, Uzair Aslam; Shoukat, Muhammad Usman; Ahmad, Raza

doi:10.3389/fpls.2022.1041514

Cited by 35 publications

(15 citation statements)

References 133 publications

(138 reference statements)

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“…Details regarding the architectures and layers of the most used NNs in image processing for object detection, classification, and segmentation are given by (Alzubaidi et al, 2021;Bhatt et al, 2021). An interesting review (Nawaz et al, 2022) presents the detection of objects in multimedia using NNs, considering singlestage detection and two-stage detection algorithms. The advantages and disadvantages related to precision, complexity, and speed of operation, in various applications such as object detection, multi-object detection, and real-time object detection, were highlighted.…”

Section: Series Of Neural Network and Their Representants For Image P...mentioning

confidence: 99%

IoT, UAV, BCI Empowered Deep Learning models in Precision Agriculture

2024

Frontiers Research Topics

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Frontiers is more than just an open access publisher of scholarly articles: it is a pioneering approach to the world of academia, radically improving the way scholarly research is managed. The grand vision of Frontiers is a world where all people have an equal opportunity to seek, share and generate knowledge. Frontiers provides immediate and permanent online open access to all its publications, but this alone is not enough to realize our grand goals. Frontiers journal seriesThe Frontiers journal series is a multi-tier and interdisciplinary set of openaccess, online journals, promising a paradigm shift from the current review, selection and dissemination processes in academic publishing. All Frontiers journals are driven by researchers for researchers; therefore, they constitute a service to the scholarly community. At the same time, the Frontiers journal series operates on a revolutionary invention, the tiered publishing system, initially addressing specific communities of scholars, and gradually climbing up to broader public understanding, thus serving the interests of the lay society, too. Dedication to qualityEach Frontiers article is a landmark of the highest quality, thanks to genuinely collaborative interactions between authors and review editors, who include some of the world's best academicians. Research must be certified by peers before entering a stream of knowledge that may eventually reach the public -and shape society; therefore, Frontiers only applies the most rigorous and unbiased reviews. Frontiers revolutionizes research publishing by freely delivering the most outstanding research, evaluated with no bias from both the academic and social point of view. By applying the most advanced information technologies, Frontiers is catapulting scholarly publishing into a new generation. What are Frontiers Research Topics?Frontiers Research Topics are very popular trademarks of the Frontiers journals series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area.

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Section: Series Of Neural Network and Their Representants For Image P...mentioning

confidence: 99%

IoT, UAV, BCI Empowered Deep Learning models in Precision Agriculture

2024

Frontiers Research Topics

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“…The identification of Industry 4.0 technologies like IoT [10], artificial intelligence [11], Cloud computing, Machine learning, Security, Big Data, Blockchain, Deep learning, Digitalization, and Cyber-physical systems [12] help organizations and policymakers identify pandemic management technologies. Moosavi et al [13] stressed digital transformation and Industry 4.0 technologies in pandemic management, suggesting they will be used in future pandemics.…”

Section: Literature Reviewmentioning

confidence: 99%

Application and management of healthcare industry 4.0 for unsafe food: Irradiation processing

Muhammad Ahmad Muneeb,

Habiba Kalsoom,

Khadija Shoukat

et al. 2023

Int. J. Sci. Res. Arch.

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Radiation technology is widely adopted in the healthcare industry 4.0 for food due to its advantages in insecticidal sterilization, reducing product microbial levels, and extending shelf life. The irradiation processing of health food mainly focuses on raw material irradiation, with less involvement in finished product irradiation. Although the national regulatory authorities have issued various regulations and standards, they still cannot meet regulatory needs. The interpretation of unsafe food should be combined with food safety standards, using a functionalist interpretation method to distinguish between substantive and non-substantive standards. This study analyzes the current application status, application basis, and regulatory policies of irradiation technology in Pakistan's health food industry, and proposes the main problems and work suggestions from the perspective of standardization. It can provide reference for the subsequent revision of national food safety standards and the construction of standard systems. This study also overviews the new innovations in industry 4.0 for food healthcare and management. Following this interpretation and application method not only helps to achieve legislative objectives, but also ensures fairness in individual cases.

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“…Details regarding the architectures and layers of the most used NNs in image processing for object detection, classification, and segmentation are given by ( Alzubaidi et al., 2021 ; Bhatt et al., 2021 ). An interesting review ( Nawaz et al., 2022 ) presents the detection of objects in multimedia using NNs, considering single-stage detection and two-stage detection algorithms. The advantages and disadvantages related to precision, complexity, and speed of operation, in various applications such as object detection, multi-object detection, and real-time object detection, were highlighted.…”

Section: Neural Network Used For Orchard Monitoringmentioning

confidence: 99%

Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic review

Popescu,

Ichim,

Stoican

2023

Front. Plant Sci.

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Orchard monitoring is a vital direction of scientific research and practical application for increasing fruit production in ecological conditions. Recently, due to the development of technology and the decrease in equipment cost, the use of unmanned aerial vehicles and artificial intelligence algorithms for image acquisition and processing has achieved tremendous progress in orchards monitoring. This paper highlights the new research trends in orchard monitoring, emphasizing neural networks, unmanned aerial vehicles (UAVs), and various concrete applications. For this purpose, papers on complex topics obtained by combining keywords from the field addressed were selected and analyzed. In particular, the review considered papers on the interval 2017-2022 on the use of neural networks (as an important exponent of artificial intelligence in image processing and understanding) and UAVs in orchard monitoring and production evaluation applications. Due to their complexity, the characteristics of UAV trajectories and flights in the orchard area were highlighted. The structure and implementations of the latest neural network systems used in such applications, the databases, the software, and the obtained performances are systematically analyzed. To recommend some suggestions for researchers and end users, the use of the new concepts and their implementations were surveyed in concrete applications, such as a) identification and segmentation of orchards, trees, and crowns; b) detection of tree diseases, harmful insects, and pests; c) evaluation of fruit production, and d) evaluation of development conditions. To show the necessity of this review, in the end, a comparison is made with review articles with a related theme.

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AI-based object detection latest trends in remote sensing, multimedia and agriculture applications

Cited by 35 publications

References 133 publications

IoT, UAV, BCI Empowered Deep Learning models in Precision Agriculture

IoT, UAV, BCI Empowered Deep Learning models in Precision Agriculture

Application and management of healthcare industry 4.0 for unsafe food: Irradiation processing

Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic review

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