Leveraging cutting-edge eye-tracking technology and machine learning algorithms, a real-time, non-invasive solution that empowers individuals with motor disabilities, allowing them to communicate seamlessly through na...
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Leveraging cutting-edge eye-tracking technology and machine learning algorithms, a real-time, non-invasive solution that empowers individuals with motor disabilities, allowing them to communicate seamlessly through natural eye movements. The project encompasses a comprehensive pipeline, starting with the collection of precise eye movement data using state-of-the-art eye-tracking hardware. It employs sophisticated image processing techniques to preprocess the acquired data, filtering out noise and detecting blink patterns accurately. This computer vision project not only showcases the potential of eye blink detection for text-based communication but also highlights the importance of innovative solutions that empower individuals with physical limitations to interact with technology effortlessly. Our recommended approach is continually used to test the effects of light and the distance between a user's eyes and a mobile device to assess the exact position, according to test results, offers 90% general exactness and 100% recognition accuracy for a distance of 15 cm with a false light.
Integrating deep learning in speech separation has revolutionized audio signal processing, impacting fields like speech recognition, audio-visual content creation, telecommunication, hearing aid technologies, etc. In ...
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Considering the varying advantages, disadvantages, and implementation difficulties of current indoor positioning algorithms, this paper conducts a comparative analysis of common UWB ranging methods. The Two-Way Rangin...
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Accurate self-localization of unmanned aerial systems (UAS) is needed to reduce their dependency on global navi-gation satellite systems (GNSS). Image retrieval techniques comparing aerial images with a reference data...
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With the development of autonomous driving technology, vehicles integrate camera, lidar, and radar modules for environment perception. In mass-produced models, cameras and lidars mostly serve as primary sensors, while...
In an increasingly globalized economy, the communication of corporate image plays a pivotal role in shaping perceptions and fostering relationships with international stakeholders. This study explores the design and i...
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This paper proposes a novel approach to video summarisation by introducing a feature variance model that enhances video frame extraction. In typical video record aggregation systems, a variety of image processing task...
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In the realm of intelligent driving, mmWave radar and camera sensors hold paramount importance. Their synergistic integration not only broadens the scope of perception but also enhances accuracy, which is pivotal for ...
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With the further research of deep learning, power companies have gradually eliminated the prevention and control by manual inspection, and have adopted deep learning to identify the safety hazards of power equipment, ...
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The proceedings contain 122 papers. The topics discussed include: DFrFT-ES model for emotion recognition based on fractional Fourier transform of EEG signals;research on traffic sign recognition under complex meteorol...
ISBN:
(纸本)9781510687615
The proceedings contain 122 papers. The topics discussed include: DFrFT-ES model for emotion recognition based on fractional Fourier transform of EEG signals;research on traffic sign recognition under complex meteorological conditions;diffusion-augmented learning for long-tail recognition;apple leaf scab recognition using CNN and transfer learning;container image management in cloud-edge environments: an image deletion method based on layer affinity;computer graphics and image processing techniques based on visualcommunication design;dynamic fusion and non-negative matrix factorization-based multi-view clustering method;convolutional recurrent neural network-based EEG signal classification in motor imagery;and sentiment classification of MOOC courses by merging local context focus and bi-directional gated recurrent unit.
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