Prolonged maintenance of poor sitting posture can have detrimental effects on human health. Thus, maintaining a healthy sitting posture is crucial for individuals who spend long durations sitting. The recent Vision Tr...
详细信息
Medical images are available in small datasets with different modalities and for various organs. Although Transfer learning is a promising approach for training models on small datasets, further studies are required o...
详细信息
Certifying software-based systems is a time-consuming and expensive task that requires much manual human effort. We introduce Online Certification, a partly automated version of the certification process, where partic...
详细信息
ISBN:
(纸本)9783031744976;9783031744983
Certifying software-based systems is a time-consuming and expensive task that requires much manual human effort. We introduce Online Certification, a partly automated version of the certification process, where participants provide the necessary information dynamically. All information is cryptographically signed to ensure integrity and authorization, and a system of certificates allows for fine-grained delegation of competencies. The requirements for certification, as well as the information needed to fulfill them, are represented in a subset of first-order logic. Consequently, validation is performed using automated logic reasoning. Compared to existing approaches, Online Certification enhances flexibility and agility. In cases where automatic generation of certification data is not possible, human certification processes can be integrated.
Foreground segmentation is an important part of computer vision and has many useful applications, such as tracking objects and detecting anomalies. However, deep learning models often struggle with the difficult task ...
详细信息
Foreground segmentation is an important part of computer vision and has many useful applications, such as tracking objects and detecting anomalies. However, deep learning models often struggle with the difficult task of preserving small details when extracting features, which is crucial for accurately segmenting edges. To overcome this challenge, we have developed a new segmentation network with a cascading architecture. This innovative approach gradually incorporates finer details into higher-level features, continuously improving the segmentation results. We have thoroughly evaluated our method using the challenging CDnet2014 dataset, and it has shown exceptional performance with an impressive F-measure of 0.9868. This research demonstrates the potential of cascading networks to greatly improve foreground segmentation in computer vision applications, and it is completely original work.
We present a new methodology for utilising machine learning technology in symbolic computation research. We explain how a well known human-designed heuristic to make the choice of variable ordering in cylindrical alge...
详细信息
ISBN:
(纸本)9783031645280;9783031645297
We present a new methodology for utilising machine learning technology in symbolic computation research. We explain how a well known human-designed heuristic to make the choice of variable ordering in cylindrical algebraic decomposition may be represented as a constrained neural network. This allows us to then use machine learning methods to further optimise the heuristic, leading to new networks of similar size, representing new heuristics of similar complexity as the original human-designed one. We present this as a form of ante-hoc explainability for use in computer algebra development.
We present a third version of the PraK system designed around an effective text-image and image-image search model. The system integrates sub-image search options for localized context search for CLIP and image color/...
详细信息
This paper concerns the computer-aided process of designing architectural objects in the form of 3D primitive configurations following the general-to-detail principle. Design objects are represented by labeled specifi...
详细信息
Speculative execution attacks affect all modern processors and much work has been done to develop techniques for detection of associated vulnerabilities. Modern processors also operate on weak memory models which allo...
详细信息
ISBN:
(纸本)9783031711619;9783031711626
Speculative execution attacks affect all modern processors and much work has been done to develop techniques for detection of associated vulnerabilities. Modern processors also operate on weak memory models which allow out-of-order execution of code. Despite this, there is little work on looking at the interplay between speculative execution and weak memory models. In this paper, we provide an information flow logic for detecting speculative execution vulnerabilities on weak memory models. The logic is general enough to be used with any modern processor, and designed to be extensible to allow detection of vulnerabilities to specific attacks. The logic has been proven sound with respect to an abstract model of speculative execution in Isabelle/HOL.
Given the incredible popularity of video games in contexts from entertainment to education, and the capacity of internet-connected games to record fine-grained telemetry data, there exists an unprecedented opportunity...
详细信息
ISBN:
(纸本)9783031741371;9783031741388
Given the incredible popularity of video games in contexts from entertainment to education, and the capacity of internet-connected games to record fine-grained telemetry data, there exists an unprecedented opportunity to investigate gameplay behaviors, outcomes, and their relationships to learning processes. However, with these opportunities come the need for technical infrastructures to manage the collection and analysis of massive amounts of game event data. In this work, we build upon existing literature to develop an architectural design for such infrastructure. We address issues of play data collection across many games;regular, repeatable extraction of gameplay features from raw data;and access to data for secondary analyses. In addition, we describe an implementation of this infrastructure and provide real-world examples of the implementation's usage in prior large-scale analysis work.
There has been a growing need to devise processes that can create comprehensive datasets in the world of computer Algebra, both for accurate benchmarking and for new intersections with machine learning technology. We ...
详细信息
ISBN:
(纸本)9783031690693;9783031690709
There has been a growing need to devise processes that can create comprehensive datasets in the world of computer Algebra, both for accurate benchmarking and for new intersections with machine learning technology. We present here a method to generate integrands that are guaranteed to be integrable, dubbed the LIOUVILLE method. It is based on Liouville's theorem and the Parallel Risch Algorithm for symbolic integration. We show that this data generation method retains the best qualities of previous data generation methods, while overcoming some of the issues built into that prior work. The LIOUVILLE generator is able to generate sufficiently complex and realistic integrands, and could be used for benchmarking or machine learning training tasks related to symbolic integration.
暂无评论