As the economic value of cryptocurrencies continues to ascend, an increasing number of cybercriminals exploit malicious browser scripts to commandeer the system and network resources of victims for unauthorized crypto...
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In Opportunistic Network based mobile data diversion algorithms, the need for multi-hop transmission makes the selection of the next hop node critical. The traditional Prophet algorithm calculates the encounter delive...
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Unlike traditional recommendation systems that rely solely on historical user-item interactions for recommendations, multimodal recommendation systems integrate multimodal features of items to enhance the accuracy of ...
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Imposing constraints on machine translation systems presents a challenging issue because these systems are not trained to make use of constraints in generating adequate, fluent translations. In this paper, we leverage...
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As extended reality becomes more ubiquitous, people will more frequently interact with computer systems using gestures instead of peripheral devices. However, previous works have shown that using traditional gestures ...
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ISBN:
(纸本)9783031355950;9783031355967
As extended reality becomes more ubiquitous, people will more frequently interact with computer systems using gestures instead of peripheral devices. However, previous works have shown that using traditional gestures (pointing, swiping, etc.) in mid-air causes fatigue, rendering them largely unsuitable or long-term use. Some of the same researchers have promoted "microgestures"-smaller gestures requiring less gross motion-as a solution, but to date there is no dataset of intentional microgestures available to train computer vision algorithms for use in downstream interactions with computer systems such as agents deployed on XR headsets. As a step toward addressing this challenge, we present a novel video dataset of microgestures, classification results from a variety of ML models showcasing the feasibility (and difficulty) of detecting these fine-grained movements, present a demonstration of a novel keyframe detection method as a way to increase recognition accuracy, and discuss the challenges in developing robust recognition of microgestures for human-computer interaction.
Human or manual transcription is the task where a person reads a handwritten document and types in a digital environment the text she is reading. The manual transcription task is a long and time-consuming process for ...
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ISBN:
(纸本)9783031347313;9783031347320
Human or manual transcription is the task where a person reads a handwritten document and types in a digital environment the text she is reading. The manual transcription task is a long and time-consuming process for one person. However, the intelligence of the transcriber is provided with better results than automatic alternatives. This article introduces a collaborative transcription platform called Transcriptor, in which the community members can upload digitized manuscripts and collaborate in transcribing them, defining different transcription layers which will be represented using semantic web technologies and gamification techniques. The article provides two experimentation that shows that Transcriptor had a good acceptance and novelty.
Learning composite concepts, such as "red car", from individual examples—like a white car representing the concept of "car" and a red strawberry representing the concept of "red"—is inh...
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Individual users on social media platforms like Twitter can significantly volatile assets, including cryptocurrencies. However, current research has overlooked this aspect, focusing on sentiment analysis that includes...
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Wildfires are one of the costliest and deadliest natural disasters in the United States, particularly in the Western USA. Wildfire frequency and severity are increasing due to climate change and urban sprawl. Detectin...
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In light of the problems associated with glare and halo effects in low-light images, as well as the inadequacy of existing processing algorithms in handling details, a glare suppression balance network based on unsupe...
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