The importance of speech emotion recognition has increased as a result of the acceptance of intelligent conversational assistant services. The communication between humans and machines may be made better via emotion r...
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As a kind of noise, speckle seriously affects the imaging quality of optical imaging system. However, the speckle image carries a large amount of information related to the physical characteristics of the object surfa...
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The image sequences captured by Unmanned Aerial vehicles (UAvs) can be applied to many computer vision tasks. However, due to the instability of UAv flight, the captured image sequences will deviate from the preset tr...
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The human brain serves as the principal controller of the humanoid system. Brain tumors are the result of abnormal cell division and proliferation, and the development of these tumors can result in brain cancer. The u...
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The goal of visual implants is to create artificial vision that can partially restore function. It can enhance the quality of life for visually challenged individuals by allowing them to feel light, even after years o...
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ISBN:
(数字)9798350372816
ISBN:
(纸本)9798350372816
The goal of visual implants is to create artificial vision that can partially restore function. It can enhance the quality of life for visually challenged individuals by allowing them to feel light, even after years of darkness, by the use of 60 microelectrodes implanted in the retina. The artificial vision that is made possible by current visual system stimulators has very poor resolution because of their small number of microelectrodes. Numerous researchers have sought to enhance artificial vision produced by low-resolution implants through the application of machine learning and imageprocessing techniques. Because phosphine pictures have low resolution, users report unhappiness with the Retinal Prosthesis System. This underscores the important need for targeted research aimed at improving visual clarity and user pleasure in general. This research proposes simulating artificial vision in which the visually impaired user receives information synthesized by the system through a low-resolution photo courtesy of a visual implant. Through the use of vision Transformer, the technique gathers useful data about people in the immediate vicinity of the visually impaired person, including their number, familiarity, gender, approximated ages, facial emotions, nearby items, and approximate distances. The information obtained from the user's glasses' camera frames is used to create signals that are then sent into a visual stimulator, offering a potentially effective way to improve the visual experience for those who are visually impaired. In order to facilitate economical real-time implementations in an independent portable system, an algorithm that best suits each feature is chosen based on its accuracy and time complexity. The proposed approach uses audio to provide crucial information about those in close proximity to a visually impaired person, enabling them to converse with others more comfortably. This paper can thus be taken into consideration for some next-generation v
Sand-dust weather causes low contrast as well as color distortions in outdoor shots, which has a significant impact on outdoor visionapplications, particularly on autonomous cars. This autonomous car system analyses ...
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Signal processing has become central to many fields, from coherent optical telecommunications, where it is used to compensate signal impairments, to video imageprocessing. imageprocessing is particularly important f...
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Signal processing has become central to many fields, from coherent optical telecommunications, where it is used to compensate signal impairments, to video imageprocessing. imageprocessing is particularly important for observational astronomy, medical diagnosis, autonomous driving, big data and artificial intelligence. For these applications, signal processing traditionally has mainly been performed electronically. However these, as well as new applications, particularly those involving real time video imageprocessing, are creating unprecedented demand for ultrahigh performance, including high bandwidth and reduced energy consumption. Here, we demonstrate a photonic signal processor operating at 17 Terabits/s and use it to process video image signals in real-time. The system processes 400,000 video signals concurrently, performing 34 functions simultaneously that are key to object edge detection, edge enhancement and motion blur. As compared with spatial-light devices used for imageprocessing, our system is not only ultra-high speed but highly reconfigurable and programable, able to perform many different functions without any change to the physical hardware. Our approach is based on an integrated Kerr soliton crystal microcomb, and opens up new avenues for ultrafast robotic vision and machine learning.
In the image super-resolution algorithm model, a large receptive field can provide more valuable features, so the Transformer with strong information interaction ability has achieved excellent results in image super-r...
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The article proposes a fusion technique and an algorithm for combining images recorded in the IR and visible spectrum in relation to the problem of processing products by robotic complexes in dust and fog. Primary dat...
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ISBN:
(纸本)9781510655461
The article proposes a fusion technique and an algorithm for combining images recorded in the IR and visible spectrum in relation to the problem of processing products by robotic complexes in dust and fog. Primary data processing is based on the use of a multi-criteria processing with complex data analysis and cross-change of the filtration coefficient for different types of data. The search for base points is based on the application of the technique of reducing the range of clusters (image simplification) and searching for transition boundaries using the approach of determining the slope of the function in local areas. As test data used to evaluate the effectiveness, pairs of test images obtained by sensors with a resolution of 1024x768 (8 bit, color image, visible range) and 640x480 (8 bit, color, IR image) are used. images of simple shapes are used as analyzed objects.
The size and the computational load of fine-tuning large-scale pre-trained neural networks are becoming two major obstacles in adopting machine learning in many applications. Continual learning (CL) can serve as a rem...
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ISBN:
(纸本)9798891760615
The size and the computational load of fine-tuning large-scale pre-trained neural networks are becoming two major obstacles in adopting machine learning in many applications. Continual learning (CL) can serve as a remedy through enabling knowledge-transfer across sequentially arriving tasks. However, existing CL algorithms primarily consider learning unimodal vision-only or language-only tasks. We develop a transformer-based CL architecture for learning multimodal vision-and-language (vaL) tasks based on dynamic model expansion and knowledge distillation. Additional parameters are used to specialize the network for each task. Our approach, Task Attentive Multimodal Continual Learning (TAM-CL), enables sharing information between the tasks while addressing catastrophic forgetting. Our approach is scalable, requiring little memory and time overhead. TAM-CL reaches SOTA performance on challenging multimodal tasks. The code is publicly available on https://***/YuliangCai2022/***.
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