The ocean comprises an uninterrupted body of salt water confined within a vast basin on the earth’s surface. The ocean is the largest ecosystem on earth with rich and diverse biological resources. Organisms that reside in salty water are referred to as “marine life.” Plants, animals, and microorganisms including archaea and bacteria are examples of these. The existence of marine life is not only a biological resource but also an economic source. Toys and other industries that imitate marine life have emerged in the market. A different modeling design of marine life has improved with the passage of time and the concept of modeling aesthetics has been incorporated. The identification of marine life images is challenging due to the complexity of the maritime environment, and there are several flaws in marine life models. The rise of deep learning has brought some new ideas for the weaknesses in marine life modeling, and the advantages of convolutional neural networks have contributed to some of the concepts based on deep learning. This research analyses marine modeling by using the benefits of convolutional neural networks, so that people can better understand marine life modeling. The experimental results indicate that the proposed approach has achieved good results in marine life detection, and the modeling effect of ocean modeling analysis based on deep learning is good.
Based on the environment of economic globalization, many clothing companies have increased the requirements for clothing design styles to diversify them, thereby increasing the interest of consumers. The main purpose and motivation are to explore the pattern design of children’s clothing with the marine bionic environment as the design source. Firstly, the collaborative business concept of IoT machine learning is introduced into the field of clothing design. Design styles and elements related to marine bionic environments are introduced. A set of questionnaires about the visual design preferences of children in different families on marine style clothing patterns are designed to examine differences in the cognitive level of color patterns among children of different age groups. Through the sorting, statistics, and analysis of the questionnaire results, different families have a stronger interest in clothing with warm colors as the color style and lines and ordinary paintings as the pattern drawing style. This provides a certain degree of design ideas for related clothing design work and provides unique insights into the visual design of brand image based on the marine bionic system in the Internet of Things (IoT) and machine learning environment.
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