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Topic Review
Biography
Topic Review
Convolutional Neural Network in the Medical Imaging
Convolutional Neural Networks (CNN), commonly known as ConvNet, is one of the common types of Artificial Neural Network (ANN) that comes under the supervised method category. This method is known for its ability to discover and interpret patterns. This pattern detection brings up the usefulness of CNN for image analysis.
756
10 Apr 2023
Topic Review
YOLO-Based Unmanned Aerial Vehicle Technology
YOLO-based unmanned aerial vehicle (UAV) technology is proposed in the context of interdisciplinary or multi-disciplinary collaborative research, by the cross-fertilization of You Only Look Once (YOLO) target detection algorithms and UAV technology. In this YOLO-based UAV technology, the UAV can provide more application scenarios for the YOLO algorithm, while the YOLO algorithm can assist the UAV with more novel tasks. The two can complement each other to further facilitate people's daily lives while contributing to the productivity of their respective industries.
864
06 Apr 2023
Topic Review
Robots in STEAM Education
Robotics is increasingly entering the field of education. The tools, methods, and approaches of robotics contribute to the development of all areas of STEAM education, both individually and interdisciplinary. The entry highlights the robots that are most effective in STEAM education and to classify robots used in education in terms of their frequency of use, features, flexibility, manufacturer, sensors, software, programming language, connection, recommended age, usefulness in education, and their cost. It turned out that there are packages for building robots, pre-assembled robots, and social robots. Their form can be animal, human, car, etc., and they have various properties; for example, they can move and fly. Moreover, most of the robots proposed for education use block-based programming; for example, the Scratch language. Common features of robots are that the robot follows a path, reacts to sounds, and recognizes obstacles, with various sensors; for example, vision. Finally, it turned out to be necessary to design an activity guide for each lesson, which will be accompanied by instructions and specific steps for teachers and students.
1.4K
06 Apr 2023
Topic Review
Deep Learning in COVID-19
Various deep-learning (DL) methods that utilize a combination of omics data and imaging data have been applied to the diagnosis, prognosis, and treatment options of clinical COVID-19 patients. Even with the emerging deep-learning methods, human intervention is still essential in the clinical diagnosis and treatment of COVID-19 patients.
477
06 Apr 2023
Topic Review
Euclidean Graphs as Curvilinear Feature Descriptors
Euclidean graphs are an ideal data structure for the functional description of line-shaped features in digital images such as cracks as they convey both geometrical and topological information about the object path in a compact and integrated format, enabling the development of autonomous, highly tuned algorithms for identification, selection, analysis, comparison and archiving of the identified objects.
808
06 Apr 2023
Biography
Yoshiyasu Takefuji
Graduated from Elec. Eng., Keio Univ. BS (1978), MS (1980), Ph.D. (1983). Asst Prof: Univ. of South Florida (1983-1985), Assoc Prof: Univ. of South Carolina (1985-1988), Assoc Prof: Case Western Reserve Univ. (1988-1996: tenured in 1992), tenured Prof: Keio Univ. (1992-2021), Emeritus Prof: Keio Univ. (2021-present), Prof: Musashino Univ. (2021-present), Docent Prof. Jyvaskyla Univ. He authors 4
1.0K
04 Apr 2023
Topic Review
Urban Computing for Sustainable Smart Cities
The proliferation of ubiquitous computing technologies has led to the emergence of urban computing that aims to provide intelligent services to inhabitants of smart cities. Urban computing deals with enormous amounts of data collected from sensors and other sources in a smart city.
320
03 Apr 2023
Topic Review
Artificial Intelligence for COVID-19 Containment
Artificial intelligence has significantly enhanced the research paradigm and spectrum with a substantiated promise of continuous applicability in the real world domain. Artificial intelligence, the driving force of the current technological revolution, has been used in many frontiers, including education, security, gaming, finance, robotics, autonomous systems, entertainment, and most importantly the healthcare sector. With the rise of the COVID-19 pandemic, several prediction and detection methods using artificial intelligence have been employed to understand, forecast, handle, and curtail the ensuing threats.
320
30 Mar 2023
Topic Review
Random Number Generation
Ever since the antiquity, random number generation has played an important role both in common everyday life activities, such as leisure games, as well as in the advancement of science. Such means as dice and coins have been employed since the ancient times in order to generate random numbers that were used for gambling, dispute resolution, leisure games, and perhaps even fortune-telling. The theory behind the generation of random numbers, as well as the ability to potentially predict the outcome of this process, has been heavily studied and exploited by mathematics, in an attempt to either ensure the randomness of the process, to gain an advantage in correctly predicting its future outcomes, or to approximate the results of rather complicated computations. Especially in cryptography, random numbers are used due to the aforementioned properties, so that attackers have no other option but to guess the secret. This fact, in conjunction with the ongoing digitalisation of our world, has led to an interest in random number generation within the framework of computer science. In this context, random number generation systems are classified into two main categories: pseudorandom number generators and true random number generators, with the former generating sequences of numbers that appear to be random, but are in fact completely predictable when the initial value (being referred to as the seed) and conditions used for the number generation process are known, and with the latter generating truly random sequences of numbers that can only be predicted (correctly) with negligible probability, even if the initial value and conditions are known.
1.1K
24 Mar 2023
Topic Review
Handwritten Chinese Text Recognition
Offline handwritten Chinese recognition is an important research area of pattern recognition, including offline handwritten Chinese character recognition (offline HCCR) and offline handwritten Chinese text recognition (offline HCTR), which are closely related to daily life. HCTR is more complex and relatively less accurate due to the unconstrained nature of text lines and the adhesion between characters. It can be further divided into line-level HCTR and page-level HCTR depending on whether the recognition object is a cropped image of a text line or an entire page.
534
24 Mar 2023
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