The proposed method is completely automatic, non-destructive, and quickly classifies the leaf images of different categories in real-time. The proposed methodology can be integrated with drones for wider crop area analysis. The convolutional neural network VirLeafNet is trained with different leaf images consisting of healthy, mild-infected, and severely infected leaves for multiple epochs. The collected image dataset of Vigna Mungo leaves belonging to different categories are segmented and augmented to introduce more variety in the leaf image dataset. Hence, it is quite challenging to make an automatic disease detection method and perform the detection tasks in real-time. Due to viral infection, some properties of the leaf image changes but the pattern is very random throughout the leaf structure. This paper proposes an automatic deep-learning-based viral infection detection method for a leguminous plant, Vigna Mungo which is grown largely in the Indian subcontinent. Thus, there is a need for developing automatic viral infection detection methods for monitoring crops and analyzing symptoms at different parts of plants. If the viral infection could be noticed at earlier stages, then recovery procedures and respective action can be taken on time. Various viral diseases affect the growth of the plants that causes a huge loss to farmers. These findings should be useful for helping broadcasters design remote production systems using a low-latency cloud network. We also found that, in all network models, SPC was better able to improve the coverage rate while satisfying the transmission-delay requirement than DPC. The results showed that the roundtrip-delay requirement was 33.4 ms (one-way transmission-delay: 16.7 ms) and that the server processing latency in the cloud should be kept in the range of 2–6 ms to satisfy the transmission-delay requirement for achieving a coverage rate of approximately 50% when using DPC and SPC for program production equipment configurations. Two different program production equipment configurations were examined: a diverse path configuration with seamless switching (DPC) and a single path configuration with forward error correction processing (SPC). In this work, to achieve remote production using a low-latency cloud, we examined the roundtrip-delay requirement for remote production and investigated which network configurations satisfied this requirement by testing network models from Japan, Europe, the USA, and China, which included metropolitan area networks. In recent years, flexible remote production systems that use cloud computing over the IP network have been considered. In remote production, a venue is connected with a broadcasting station by an IP network, and live programs are produced not on the venue side but on the broadcasting station side. With the shift to the Internet Protocol (IP) in professional media production, the demand for a remote professional media production system (hereinafter “remote production”) is increasing. It has been mounted mostly on Linux environments to guarantee reliability and the extensive use of free software, which demonstrates the feasibility of building a cost-effective video-audio production mixer, using the available devices and techniques. Although it works on non-dedicated hardware, this system provides video routing, sound managing, and audiovisual mixing with an approximate total delay of only 1.4 s. This technology has been mounted using different high-definition cameras with High-Definition Multimedia Interface (HDMI) outputs, desktop computers, mobile phones and other non-dedicated equipment available for free or at a low cost. The system also features a voice intercommunication capability to support teamwork. A prototype combining five cameras, a title generator, a multimedia player, microphone sound, music, and other resources for video recording or Internet live streaming has been implemented. It is presented as a potential replacement for traditional professional production systems on the basis of cost reduction, as it is a software-based system that uses the existing technologies and can be built in community television stations and economic private productions. This paper describes the design and implementation of a video-audio production mixer via an IP network. Modern television production has promoted the simultaneous use of several cameras and sound sources, which increases the complexity and costs of broadcasting studios.
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