Guest Editors
Dr. Mohammad Tabrez Quasim, University of Bisha, Saudi Arabia.
Dr. Surbhi Bhatia, King Faisal University, Saudi Arabia.
Dr. Fahad Alqarni, University of Bisha, Saudi Arabia.
Dr. Kapal Dev, University of Johannesburg, South Africa.
Dr. Mohammad Alojail, King Faisal University, Saudi Arabia.
Summary
Applied Artificial Intelligence techniques have proven to be efficient and flexible at solving dynamic and complex real-world problems. The multimedia content consisting of image and video data is abundantly shared online including numerous amount of datasets. The plethora of techniques under the banner of applied artificial intelligence (AI) includes Machine Learning, Neural Networks, Deep Learning, Fuzzy Logic, Evolutionary Computation, Intelligent Agent Systems, Cellular Automata, Game Theory, and other similar systems. The use of these techniques has enabled the development of robust decision support systems across numerous fields. The combination of multimedia and applied AI in agriculture, food production, and its security, environmental sustainability will open vast areas of research for multimedia-rich applications such as video streaming, farming, organic cultivation, diseases, pests control, diagnosis, and so forth. Since the new multimedia data keeps growing exponentially, the applied AI techniques will be useful to come up with robust solutions for decision making. For example, how to collect data and related information in real-time, and how to rapidly process a large amount of multimedia data using image processing techniques, and further to apply the applied artificial intelligence techniques to achieve desirable performances in terms of both accuracy and efficiency.
Thus, for this special issue, deeply investigated works describing both theoretical and practical evaluations related to the design, analysis, and implementation of technologies for image processing in healthcare, agriculture, and environmental sustainability in multimedia systems are invited.
Keywords
Image processing and acquisition techniques
Image computing convergence
Machine learning for IoT devices in agriculture
Machine learning for IoT devices in the Food Supply chain
AI-enabled secure AgriFood
Deep Learning approach for environment sustainability
Applied AI in real-time analytics
Data analytics for multimedia big data systems in agriculture, food security
Image, audio, and video compression standards for AgriFood
AI in predictive analytics
AI for future Computing vision-based approaches
Innovations in multimedia systems for agriculture
Published Papers
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Open Access
ARTICLE
Plant Identification Using Fitness-Based Position Update in Whale Optimization Algorithm
Ayman Altameem, Sandeep Kumar, Ramesh Chandra Poonia, Abdul Khader Jilani Saudagar
CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4719-4736, 2022, DOI:10.32604/cmc.2022.022177
（This article belongs to this Special Issue:
Recent advancements in Environment Sustainability, AgriFood using applied artificial intelligence in Multimedia Systems)
Abstract Since the beginning of time, humans have relied on plants for food, energy, and medicine. Plants are recognized by leaf, flower, or fruit and linked to their suitable cluster. Classification methods are used to extract and select traits that are helpful in identifying a plant. In plant leaf image categorization, each plant is assigned a label according to its classification. The purpose of classifying plant leaf images is to enable farmers to recognize plants, leading to the management of plants in several aspects. This study aims to present a modified whale optimization algorithm and categorizes plant leaf images into classes.…
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