A Feature In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Nashville, TN, USA, 2025 June 2021; pp. Decomposition breaks down problems into smaller, more manageable parts. We see this in compression of text files, photos and videos, and often the computers will compress when doing backups. ; software, J.H. Your alarm on your smart phone wakes you in the morningthats powered by computer science. Experiments on different datasets show that the enhanced image can achieve higher PSNR and SSIM values, and the mAP value also achieved significant results in the object detection task. Read more about Shannons Information Theory and Computational Thinking in my new book, also publicly viewable on ResearchGate. For example, you might want to search for students in a class, or who are being taught by a specific teacher all these involve some form of searching, the only thing that differs is what you are searching for. Abstraction is similar to the selective filtering function in our brains that gates the neural signals with which we are constantly bombarded so we can make sense of our world and focus on whats essential to us. Abstraction in computational thinking enables us to navigate complexity and find relevance and clarity at scale. (1991). We chose the pre-trained YOLOv5 as the object detection model and tested the images before and after enhancement on the EUVP dataset. Scientific Reports, 10(1), 110. A cognitive definition of computational thinking in primary education. This pattern can then be applied to any systems that tracks and monitors student data, including attendance, punctuality and recording homework marks. Incorporating computational thinking into how I think about and plan my design projects helps eliminate unnecessary paths that will not work, which is a time saver. Cognitive load theory (Sweller, 1988) suggests that we each have a limited capacity to hold different concepts in 'working memory' when problem-solving, with the implication that when programming problems involve too many different elements, this capacity can be exceeded.Students will then have increasing difficulty in solving such problems. Pattern recognition is based on the 5 key steps of: Identifying common elements in problems or systems, Identifying and Interpreting common differences in problems or systems, Identifying individual elements within problems, Describing patterns that have been identified. This process occurs through filtering out irrelevant information and identifying whats most important. Electronics | Free Full-Text | FE-GAN: Fast and Efficient Underwater As shown in. In this dataset, part of the images are collected by seven different camera equipment; the other part comes from images captured in YouTube videos. In software engineering and computer science, abstraction is a technique for arranging complexity of computer systems. Can you think of any generalisation of processes between the two? Another way to think about abstraction is in the context of those big concepts that inform how we think about the world like Newtons Laws of Motion, the Law of Supply and Demand, or the Pythagorean Theorem. Our web-based curriculum for grades K-12 engages students as they learn keyboarding, online safety, applied productivity tools, computational thinking, coding and more. The pattern recognition in each area provides a scaffold for the total solution. ; writingreview and editing, J.H. This paper proposes a fast and efficient underwater image enhancement model based on conditional GAN with good generalization ability using aggregation strategies and concatenate operations to take full advantage of the limited hierarchical features. Here we used mAP (mean average precision) as a reference metric. Zhang, L.; Li, C.; Sun, H. Object detection/tracking toward underwater photographs by remotely operated vehicles (ROVs). Computers store and enormous amount of data and in so doing they utilize algorithms that simply use pointers or markers instead of repeated lines of text or data. 67236732. In Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy, 2229 October 2017; pp. Over the last several years, many AUVs and ROVs have been applied to ship hull inspection, underwater target detection and tracking [, Natural light is absorbed and scattered when propagating in seawater. If you were to look at how your day is organised in your School or College, you will see that it follows a pattern: This pattern holds true for each day of the week for most students in most schools and colleges. The details of the hierarchical attention encoder (HAE) are shown in, For the discriminator, we use a Markov discriminator [, The conditional generative adversarial network introduces additional auxiliary information and can learn the mapping. Understanding abstraction enables students to make sense of problems they encounter, helping them to not be overwhelmed in the face of something complex and to persist, compute, iterate, and ideate. One system might simply record present and absent. For example, you might want to search for a student in a school IMS. Seeing is understanding: The effect of visualisation in understanding programming concepts. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA, 2730 June 2016; pp. UIQM is expressed as a linear combination of these three indexes. Under the same experimental conditions, the test results using the aggregation operation method perform better in both PSNR and SSIM values. These heuristics for computational thinking are very similar to the heuristics usually given for the 5-step scientific method taught in grade school, which is often written out as something like: These are nice guidelines but theyre not mandatory. Education and information technologies (2022) 27:8289-8310 It can also expand the difference between the features of different objects in the image, improve the image quality, enrich the amount of information, and strengthen the recognition effect. PDF Promoting Undergraduate Pre-Service Teacher Computational Thinking and J.Z. and pattern recognition break down the complex, while abstraction figures out how to work with the different parts efficiently and accurately. In Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 2125 May 2018; pp. Another example of abstraction might be creating a summary of a book or movie. We also know that an algorithm is an effective procedure, a sequence of step-by-step instructions for solving a specific kind of problem using particular data structures, which designate specific data representations. Visit our dedicated information section to learn more about MDPI. Tsarava, K., Moeller, K., Romn-Gonzlez, M., Golle, J., Leifheit, L., Butz, M. V., & Ninaus, M. (2022). In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, LA, USA, 21 June 2022; pp. IGI Global. These rules, in turn, can directly inform the final algorithm well use in the second step of constructing the computational solution. and Y.W. permission is required to reuse all or part of the article published by MDPI, including figures and tables. As students go through the learning process, they are exposed to many type of patterns and the early recognition of patterns is key to understanding many other more complex problems. For the Mixed dataset, we selected Test-R90 (90 paired images) and Test-C60 (60 unpaired images) as the test sets of paired and unpaired images respectively and compared them with the same methods in qualitative evaluation. 22232232. It hides the underlying complexity in a programming language, which makes it simpler to implement algorithms and communicate with digital tools. What are the patterns we can recognize? We can then think of programs as being the computational solutions, the solutions to computable functions, that we express in some particular programming language. In addition, we downloaded the Aquarium Combined dataset, then trained and tested this dataset on the same hardware environment as the FE-GAN enhancement experiment. In this approach, we can also think of the Principles as the Strategy, the high level concepts needed to find a computational solution; the Ideas can then be seen as the particular Tactics, the patterns or methods that are known to work in many different settings; and, finally, the Techniques as the Tools that can be used in specific situations. Using a public data set we will examine patterns in data and visualize or describe the patterns. In recent years, many learning-based methods used, Structural reparameterization is used in our encoder to speed up inference. Cognition and Instruction, 8(4), 293332. [. ;Zg-Zz2|#W%,/@$`VQ Once you have decomposed a complex problem, it helps to look for similarities or 'patterns' in each segmented part of the problem. All cats have similar characteristics. Results on different datasets prove that the model also has good generalization ability. The processing of underwater images can vastly ease the difficulty of underwater robots' tasks and promote ocean exploration development. Abstraction principle (computer programming). Google Scholar. Li, Y.; Lu, H.; Zhang, L.; Li, J.; Serikawa, S. Real-time visualization system for deep-sea surveying. You are accessing a machine-readable page. Of course not, your computer just turns itself on. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 1823 June 2018; pp. Sweller, J. However, the training process of GAN is usually unstable. Papadakis, S., Kalogiannakis, M., Orfanakis, V., & Zaranis, N. (2019). Pattern recognition as part of computational thinking is the process of identifying patterns in a data set to categorize, process and resolve the information more effectively. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA, 2126 July 2017; pp. We chose fps as a metric to measure inference time, which expresses as, For AUVs and ROVs, during underwater exploration activities, the purpose of improving the image quality is to improve the accuracy of tasks such as object detection and classification. Compared with the original distorted image, the processed image has a more natural tone and increased brightness, so the target in the image is clearer and easier to identify.