Among hepatocellular carcinoma (HCC), early HCC such as well-differentiated hepatocellular carcinoma is more difficult to distinguish from non-cancer than other cancers. In particular, very well-differentiated hepatoc...
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ISBN:
(纸本)9798350324471
Among hepatocellular carcinoma (HCC), early HCC such as well-differentiated hepatocellular carcinoma is more difficult to distinguish from non-cancer than other cancers. In particular, very well-differentiated hepatocellular carcinoma is even more difficult to distinguish, and it is difficult for pathologists to distinguish between cancer and non-cancer from a single nucleus image. If a function to distinguish cancer with a single cell nucleus image is realized, it may be possible to find new features related to nuclei that are useful for differentiating early HCC. The function will also be very helpful in needle biopsy where the area that can be observed is limited. In this study, we investigated the potential to discriminate cancer/non-cancer from an image of a single hepatocyte nucleus using CNN. The results indicated that discrimination was achievable with a correct rate of around 70%. The probability of cancer/non-cancer was visualized on WSI. The visualization results indicated a difference between cancerous and non-cancerous areas in 71% of the cases, which will help pathologists distinguish region of interest. Grouping sections with similar features also proved useful in improving accuracy and visualization results.
Procurement is an important link in the supply chain. Sustainable procurement has emerged as a crucial strategy to address environmental and social challenges while promoting responsible sourcing and procurement pract...
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The expanding realm of eXtended Reality (XR) has witnessed a surge in 3D experiences across diverse domains, undergoing significant transformations to define novel experiences. However, such experiences are often buil...
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ISBN:
(纸本)9798350374490;9798350374506
The expanding realm of eXtended Reality (XR) has witnessed a surge in 3D experiences across diverse domains, undergoing significant transformations to define novel experiences. However, such experiences are often built from scratch, as there is a lack of tools that support augmenting existing non-immersive interfaces, like Desktop games and simulators, directly into XR. Such shortage is particularly exacerbated in the case of Mixed Reality (MR). Motivated by this, we present a novel middleware, Flying In XR (FIXR), leveraging Deep Learning to visualize and interact with desktop application views into XR. To demonstrate the flexibility of such an approach, we applied FIXR to a commercial Desktop flight simulator, supporting an MR experience. It is worth noticing that FIXR could be adapted to communicate with any desktop software with a camera that moves along the depth axis, opening new paths to enable user experiences in XR for a wide spectrum of applications.
Video Question Answering (Video QA) is a task to answer a text-format question based on the understanding of linguistic semantics, visual information, and also linguisticvisual alignment in the video. In Video QA, an ...
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ISBN:
(纸本)9781665493468
Video Question Answering (Video QA) is a task to answer a text-format question based on the understanding of linguistic semantics, visual information, and also linguisticvisual alignment in the video. In Video QA, an object detector pre-trained with large-scale datasets, such as Faster R-CNN, has been widely used to extract visual representations from video frames. However, it is not always able to precisely detect the objects needed to answer the question because of the domain gaps between the datasets for training the object detector and those for Video QA. In this paper, we propose a text-guided object detector (TGOD), which takes text question-answer pairs and video frames as inputs, detects the objects relevant to the given text, and thus provides intuitive visualization and interpretable results. Our experiments using the STAGE framework on the TVQA+ dataset show the effectiveness of our proposed detector. It achieves a 2.02 points improvement in accuracy of QA, 12.13 points improvement in object detection (mAP50), 1.1 points improvement in temporal location, and 2.52 points improvement in ASA over the STAGE original detector.
Self-Organizing Map (SOM) is one of the neural networks employed, particularly in data mining and related fields. Like Deep Learning, SOM requires iterative calculations of a vast number of high-dimensional vectors. C...
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While mathematical formulas are widely applied across various fields, the abundance of information they contain poses challenges for comprehension. Understanding the meanings of individual symbols in formulas is a sig...
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Trading for a currency pair on centralized crypto exchanges is organized via an order book, which collects all open buy and sell orders at any given time and thus forms the basis for price formation. Usually, the exch...
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ISBN:
(纸本)9798350310191
Trading for a currency pair on centralized crypto exchanges is organized via an order book, which collects all open buy and sell orders at any given time and thus forms the basis for price formation. Usually, the exchanges provide basic visualizations, which show the accumulated buy and sell volume in an animated 2D representation. However, this visualization does not allow the user to compare different order books, e.g., several order book snapshots. In this work, we present OrderBookVis, a 2.5D representation that shows a discrete set of order books comparatively. For this purpose, the individual snapshots are displayed as a 2D representation as usual and placed one after the other on a 2D reference plane. As possible use cases, we discuss the analysis of the temporal evolution of the order book for a fixed market and the comparison of different order books across multiple markets.
Virtual Reality (VR) has found application in many fields including art history, education, research, and smart industry. Immersive 3D screens, large-scale displays, and CAVE systems are time-tested VR installations i...
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ISBN:
(纸本)9798350348392
Virtual Reality (VR) has found application in many fields including art history, education, research, and smart industry. Immersive 3D screens, large-scale displays, and CAVE systems are time-tested VR installations in research and scientific visualization. In this paper, we present learnings and insights from ten years of operating and maintaining a visualization center with large-scale immersive displays and installations. Our report focuses on the installations themselves as well as the various developments of the center over time. In addition, we discuss the advantages, challenges, and future development of a location-based VR center.
The concept of data-centered companies is of rapidly increasing interest within the process industry due to applications like data analysis, plant optimization and visualization. However, chemical companies face high ...
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ISBN:
(纸本)9781665493130
The concept of data-centered companies is of rapidly increasing interest within the process industry due to applications like data analysis, plant optimization and visualization. However, chemical companies face high barriers regarding the wide variety and heterogeneity of data along the brownfield plant lifecycle caused by the long history of tool-focused enterprises. This paper proposes an information Model architecture for the process industry and an approach to overcome the hurdles associated with brownfield plants and information mapping.
In today's data-driven world, the ability to collect and analyze data from remote servers has become an essential task for various industries. With the exponential growth of data, organizations require efficient a...
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