https://doi.org/10.3390/electronics12051227, Han, Jie, Jian Zhou, Lin Wang, Yu Wang, and Zhongjun Ding. Volume 12, Issue 1, pages 540549, ISSN 22178309, DOI: 10.18421/TEM12164, February 2023. In this dataset, part of the images are collected by seven different camera equipment; the other part comes from images captured in YouTube videos. 2023 Springer Nature Switzerland AG. If the problem is some complex task, you might break it down into a sequence of simpler sub-tasks. the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, This approach is often called computational thinking and is similar, in many ways, to the scientific method where were concerned with making predictions. and Z.D. Or if you see a consistent trend upward in a stock for a number of months, you might decide to buy some shares in that stock. Du, Z.; Liu, D.; Liu, J.; Tang, J.; Wu, G.; Fu, L. Fast and Memory-Efficient Network Towards Efficient Image Super-Resolution. 49524956. 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. Defining Computational Thinking as an Evident Tool in Problem-Solving Next, we will try to optimize more network modules with structural reparameterization to improve the enhancement effect of the model on images with insufficient brightness, and focus on the practical application in underwater object detection and scene analysis. School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China, Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks, Wuhan 430070, China, National Deep Sea Center, Qingdao 266237, China. Here, we also chose PSNR and SSIM as the evaluation indicators that regard aggregation and concatenate as the connection mode between the encoder and the decoder. How Computational Thinking Can Help You to Design Better Compare Google Maps to a physical map vs GPs systems. Here we used mAP (mean average precision) as a reference metric. See further details. Li, C.; Guo, C.; Ren, W.; Cong, R.; Hou, J.; Kwong, S.; Tao, D. An underwater image enhancement benchmark dataset and beyond. As a crucial processing technology in the field of computer vision, image enhancement can purposefully emphasize the holistic or partial characteristics of an image. Computational Thinking Defined - Towards Data Science xJSmSr!@67gQ Ai Founded in 1999, Learning.com provides educators with solutions to prepare their students with critical digital skills. 234241. What Is Computational Thinking? - Computational Thinking for High There may be kids running around the classroom or making loud noises, but they can tune that out to focus on what the kid in need is asking until of course it reaches an apex level of rambunctiousness and an intervention must be had. The appropriateness of scratch and app inventor as educational environments for teaching introductory programming in primary and secondary education. Arts: Students generalize chord progressions for common musical genres into a set of general principles they can communicate. Abstraction principle (computer programming). It was proposed by Ref. [, Ding, X.; Zhang, X.; Ma, N.; Han, J.; Ding, G.; Sun, J. Repvgg: Making vgg-style convnets great again. Zeng, L.; Sun, B.; Zhu, D. Underwater target detection based on Faster R-CNN and adversarial occlusion network. We can also codify this information in some knowledge-based system that is curated using knowledge management techniques. We apply the FE-GAN model to real and artificially synthesized underwater image datasets, process paired and unpaired distorted images, and compare them with the corresponding ground truth images. Another system might record, present, planned absence, unplanned absence and late. All authors have read and agreed to the published version of the manuscript. It hides the underlying complexity in a programming language, which makes it simpler to implement algorithms and communicate with digital tools. Seeing is understanding: The effect of visualisation in understanding programming concepts. Zhang, H.; Sun, L.; Wu, L.; Gu, K. DuGAN: An effective framework for underwater image enhancement. ; Wang, Z.; Paul Smolley, S. Least squares generative adversarial networks. [. Learn more about abstraction in computational thinking by downloading our free guide for educators: The Ultimate Guide to Computational Thinking for Educators, How to Help Students Improve Pattern Recognition Skills, 3 Important Additions to Digital Literacy for Students in 2023. The main contributions of this paper are as follows: We present a hierarchical attention encoder (HAE) to fully extract texture detail information, and a dual residual block (DRB) can more efficiently utilize residual learning to accelerate network inference. Let's examine some other common problems. What is the best way to present the information. Circuits Syst. captured are operated to obtain the clear images as the desired output [. We dont care HOW they do them only that they work. Computational thinking is a problem-solving skill set that is used to tackle problems in computer science. The conversion of Data to Information and then Knowledge can be done via computational problem solving. Electronics. Computational thinking is the process of defining a step-by-step solution to a complex problem or to achieve a specific goal. equip is an editorial to help you teach, prepare, and empower students to thrive in a connected and digital world. [. Students generalize chord progressions for common musical genres into a set of general principles they can communicate. We will look at searching algorithms later on in the course. While the phrase . Abstraction in coding and computer science is used to simplify strings of code into different functions. (2010). You may or may not be set homework for a particular lesson. Abstraction helps students return to the larger problem that prompted this whole computational thinking adventure and identify the most important details from the earlier phases. Although these are differences, all School and College IMS systems fundamentally need to be able to take a register. One system might simply record present and absent. 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. Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive We chose the pre-trained YOLOv5 as the object detection model and tested the images before and after enhancement on the EUVP dataset. Such systems are known as Information Management Systems (IMS). As technology advances and adapts faster and Computational thinking is problem-solving. Your home for data science. Students develop laws and theorems by looking at similar formulas and equations. In driving, we use pattern recognition to predict and respond to different traffic patterns processes. Panetta, K.; Gao, C.; Agaian, S. Human-visual-system-inspired underwater image quality measures. ?^MS1 1Xo=08?=P424!G0&Af I 5kLb5b&qBp# fK//B6llt nK_2e" ! Lets look at how to actually find such a computational solution with the caveat that individual steps will be customized as different problems will require different detailed approaches. Springer, Cham. A hierarchical attention encoder (HAE) can extract deeper features and texture information, while preserving the overall structure of the image. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 1823 June 2018; pp. 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. Patterns exist between different problems and within a single problem. ; Key Processes - these are the things that are critical to the system - for . In the case of the school register, the input will be a Character entered against the student name It could be / or P if the student is present, and N, \ or L if they are not present. Theyre suggestions of ideas youll likely need or require for most efforts but its not some process to pigeonhole your thinking or approach to a solution. In recent years, many learning-based methods used, Structural reparameterization is used in our encoder to speed up inference. [, Zhu, J.Y. If the problem deals with a complex system, you might break the system down into a bunch of smaller sub-components. While pattern recognition is most commonly discussed as a step in computational thinking, we automatically use pattern recognition in our everyday lives. 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. White, G. L. (2001). Although computational thinking isnt a formal methodology for reasoning, it does encompass some basic principles that are useful in all fields and disciplines. New diseases can also be categorized and have cures, treatments, or preventions identified based on pattern recognition from other corresponding medical complications. We will relate these examples to modern solutions that deal with many more data items. and J.Z. and J.Z. Students conduct a survey of peers and analyze the data to note the key findings, create visualizations, present the findings. Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. Pattern recognition is an essential tool in computational thinking in computer science as well as in everyday life. (eds) Teaching Coding in K-12 Schools. The University of Texas at Austin. Patterns are things that are the same within a problem and between problems. A cognitive definition of computational thinking in primary education. Element interactivity and intrinsic, extraneous, and germane cognitive load. What is Pattern Recognition in Computational Thinking? I can communicate the key features of problems and processes to others. Our web-based curriculum for grades K-12 engages students as they learn keyboarding, online safety, applied productivity tools, computational thinking, coding and more. hb```f``*c`e` B@16L< Computational Thinking - Pattern Recognition - Google Zhang, H.; Zhang, S.; Wang, Y.; Liu, Y.; Yang, Y.; Zhou, T.; Bian, H. Subsea pipeline leak inspection by autonomous underwater vehicle. (2000). The authors declare no conflict of interest. It works by establishing a level of complexity on which a person interacts with the system, suppressing the more complex details below the current level. Li, Y.; Lu, H.; Zhang, L.; Li, J.; Serikawa, S. Real-time visualization system for deep-sea surveying. Learn about the four cornerstones of computational thinking including decomposition, pattern recognition, abstraction and algorithms. Sinha, A., & Vessey, I. Sweller, J. Consider early arithmetic patterns for addition and multiplication using time tables. In Proceedings of the European Conference on Computer Vision, Amsterdam, The Netherlands, 1114 October 2016; pp. Even if a computational solution cannot be repeated in whole for a different problem or goal, pattern recognition can help identify parts of different problems that may be resolved using pieces of other solutions. In Proceedings of the International Conference on Computer Vision, Venice, Italy, 2229 October 2017; pp. In computational thinking, decomposition and pattern recognition break down the complex, while abstraction figures out how to work with the different . It is mainly composed of three parts: luminance, contrast, and structure contrast. 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. https://doi.org/10.1007/978-3-031-21970-2_26, Shipping restrictions may apply, check to see if you are impacted, http://rigaux.org/language-study/diagram.html, Tax calculation will be finalised during checkout. The processing of underwater images can vastly ease the difficulty of underwater robots' tasks and promote ocean exploration development. [. Once you have identified a pattern you can speculate whether it can be reused in your existing program, or used in another program. For example, you might want to search for a student in a school IMS. ; Li, K.; Luan, X.; Song, D. Underwater image co-enhancement with correlation feature matching and joint learning. Underwater image enhancement via physical-feedback adversarial transfer learning. Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. SSIM is a metric used to measure the similarity of images, and it can also be used to judge the quality of images after compression. ; Zhao, X.; Cosman, P.C. Han, J.; Zhou, J.; Wang, L.; Wang, Y.; Ding, Z. FE-GAN: Fast and Efficient Underwater Image Enhancement Model Based on Conditional GAN. hko Each participant at this workshop may have used Google Maps to arrive here today the algorithm generated to provide you the detailed instructions is based on pattern recognition. future research directions and describes possible research applications. "FE-GAN: Fast and Efficient Underwater Image Enhancement Model Based on Conditional GAN" Electronics 12, no. 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. Nayar, S.K. IEEE. [, Spier, O.; Treibitz, T.; Gilboa, G. In situ target-less calibration of turbid media. Abstraction means hiding the complexity of something away from the thing that is going to be using it. This is a similar problem to bringing utilities to each home, a situation engineers face when building communities. Editors select a small number of articles recently published in the journal that they believe will be particularly To quantitatively analyze the enhancement effect of the FE-GAN model on the paired underwater image, we choose PSNR (peak signal-to-noise ratio) and SSIM (structural similarity) as reference indicators. 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. No special Its a drawing of a pipe. Pattern recognition is prominent in medicine, where identifying patterns helps to diagnose and cure diseases as well as to understand and prevent disease. Most participants will have navigated their way to this workshop and this is in itself a pattern recognition issues, mostly a transportation problem and an algorithmic design component as well. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA, 2730 June 2016; pp. Recognizing a pattern, or similar characteristics helps break down the problem and also build a construct as a path for the solution. Why Is Computational Thinking Important for Students? This is based on pattern recognition, similar to fingerprints. ; Narasimhan, S.G. In Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy, 2229 October 2017; pp. The elements can be broken down into inputs, processes and outputs. So to summarise what we have learned in this lesson: Pattern Recognition, Generalisation & Abstraction, https://www.tutorialspoint.com/design_pattern/design_pattern_overview.htm, Representing parts of a problem or system in general terms, It will be broken up into a number of lessons of a set length, You will have a lesson with a teacher and the teacher will take a register. Think of your two favourite games. When a patient discusses symptoms with a doctor or undergoes a series of tests, the results are compared against known patterns to quickly identify types of infections or injuries that may be causing the symptoms and to apply corresponding solutions to the diagnoses. For example, if youre driving on the freeway and you notice cars bunching together in the left lane down the road, you might decide to change into the right lane. Consider the student search system, it can be represented using the following terms: Think back to your student planner program from Lesson 1. Jaffe, J.S. Anna is also an avid baker and self-described gluten enthusiast, a staunch defender of the oxford comma, and a proud dog mom to two adorable rescue pups. After Jeanette Wing in 2006 described computational thinking (CT) as a fundamental skill for everyone just like reading or arithmetic, it has become a widely discussed topic all over the world. 694711. In software engineering and computer science, abstraction is a technique for arranging complexity of computer systems. Two different Student IMS systems might have different ways of taking a register. These rules, in turn, can directly inform the final algorithm well use in the second step of constructing the computational solution. This process occurs through filtering out irrelevant information and identifying whats most important. Your task is to create the algorithm that will have the knight visit each square without going off the board. In computational thinking, one of the integral steps to the problem-solving process is pattern recognition. Inspired by this trend, some scholars proposed to use the computing power of convolutional neural networks to calculate the parameters that need to be estimated in the physical imaging model [, The emergence of the GAN (generative adversarial network) opened up another path for image enhancement issues. Pixel-level: Existing research shows that the, The model we proposed uses paired image training, and an objective function is constructed for this purpose to guide. and pattern recognition break down the complex, while abstraction figures out how to work with the different parts efficiently and accurately. Through structural re-parameterization, we equate complex modules to simple convolutional layers, which accelerates the model during inference while maintaining a good enhancement effect. Li, C.; Anwar, S.; Hou, J.; Cong, R.; Guo, C.; Ren, W. Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding. ; Park, T.; Isola, P.; Efros, A.A. Unpaired image-to-image translation using cycle-consistent adversarial networks. In addition, being able to identify the general principles that underly the patterns weve identified allows us to generalize patterns and trends into rules. Uoi|^;KAzMe}_-wmF~8|7osQw{SW"hog+`9T*#AcIiHm#H!7Ix./2N)##%i}>.J4gnFQte < 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. In this section, we chose a relatively complete set of real and artificial synthetic underwater images to test the enhancement effect of the proposed model. Disclaimer/Publishers Note: The statements, opinions and data contained in all publications are solely Ever find yourself saying, 'where have I seen this before', could be a significant step in computational thinking. ; Shahri, A.M. Have a look at the following website about the Gang of Four design patterns https://www.tutorialspoint.com/design_pattern/design_pattern_overview.htm. This process occurs through filtering out irrelevant information and identifying whats most important. 12221230. Several aspects should be taken into consideration, such as FLOPs, number of parameters, and inference time during deploying on resource-limited devices. Ronneberger, O.; Fischer, P.; Brox, T. U-net: Convolutional networks for biomedical image segmentation. Our web-based curriculum for grades K-12 engages students as they learn keyboarding, online safety, applied productivity tools, computational thinking, coding and more.
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