The proliferation of smart devices and related technologies has made the Internet of Things(IoT) the most rapidly emerging technology of the past ten years, both in terms of industrial applications and research opport...
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Integrating High-Performance Computing (HPC) with Artificial Intelligence (AI) has greatly expanded the area of protein-protein interaction (PPI) analysis, which is essential for comprehending biological processes. In...
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Semantic Textual Similarity (STS) plays a critical role in various natural language processing (NLP) applications such as information retrieval, text summarization, and machine translation. This paper presents a compr...
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This paper describes the image selection method for an efficient three-dimensional (3D) reconstruction computation from an image sequence. Adequate images must be selected from the image sequence to improve the comput...
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ISBN:
(纸本)9781665445405
This paper describes the image selection method for an efficient three-dimensional (3D) reconstruction computation from an image sequence. Adequate images must be selected from the image sequence to improve the computational efficiency of the 3D reconstruction. Thus, we investigated a threshold based on the displacement among images obtained from a camera mounted on a remotely operated robot. The results confirmed that the proposed method can select adequate images for efficient 3D reconstruction by the threshold based on the optical flow from the image sequence. Therefore, the computational cost could be reduced by eliminating the duplicate and high-similarity images to perform the efficient 3D reconstruction.
Edge caching is a promising technique for effectively reducing backhaul pressure and content access latency in the Internet of Vehicles (IoV). However, the high mobility of vehicles and dynamic user requests often lea...
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The three V's, namely volume, velocity and variety of sensor data are ubiquitous for decision-making in autonomous self-driving vehicles. The sensor data contain information about living and non-living entities in...
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ISBN:
(纸本)9781665457132
The three V's, namely volume, velocity and variety of sensor data are ubiquitous for decision-making in autonomous self-driving vehicles. The sensor data contain information about living and non-living entities in the neighbourhood of the moving vehicle. While identifying these objects are essential, details such as human faces, vehicle number plates, building names, etc., are not necessary for decision-making. Thus, we consider the following issues related to data collection, 1) the problem of data privacy, and 2) the problem of misuse of data by an adversary having unauthorized access. This paper proposes a method that first locates private objects (non-essential for decision-making) from frames captured by cameras installed on self-driving cars and then augments it with noise and blurring effects to make them unrecognizable. The performance results show that a combination of blurring and noise can hide private data while retaining information essential for the car to drive. Also, as the proposed approach processes within the limits of the interframe capture time, it is feasible for use in ***, results show that the proposed method can defend the adversarial attacks for the reconstruction of image frames from a given augmented frame.
For the deaf community, sign language is an essential means of communication. It is a three-dimensional language that uses hands that move dynamically and visually to represent letters and words. The field of gesture ...
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Relevance modeling is a critical component for enhancing user experience in search engines, with the primary objective of identifying items that align with users’ queries. Traditional models only rely on the semantic...
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Intrusion Detection Systems play an important role in network security. With the advent of Machine Learning and Artificial Intelligence, ML-based IDS have been gaining increasing popularity in comparison with traditio...
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We tackle Paragraph-level Question Generation (abbr., PQG) in this paper. PQG is a task of automatically generating questions given paragraphs and answers. Identifying the relevant sentences to answers is crucial for ...
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