image captioning is the task of generating a textual description that accurately represents the content of an image. this task involves combining computervision techniques, such as object recognition and scene unders...
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the proceedings contain 11 papers. the topics discussed include: toward objective variety testing score based on computervision and unsupervised machine learning: application to apple shape;using deep learning for th...
ISBN:
(纸本)9789897586934
the proceedings contain 11 papers. the topics discussed include: toward objective variety testing score based on computervision and unsupervised machine learning: application to apple shape;using deep learning for the dynamic evaluation of road marking features from laser imaging;Belfort birth records transcription: preprocessing, and structured data generation;fitting tree model with CNN and geodesics to track blood vessels in 2D medical images and application to ultrasound localization microscopy data;production-ready end-to-end visual quality inspection for defect detection on surfaces based on a multi-stage ai system;multimodal deepfake detection for short videos;HERO-GPT: zero-shot conversational assistance in industrial domains exploiting large language models;leveraging temporal context in human pose estimation: a survey;and chaotic convolutional long short-term memory network for respiratory motion prediction.
Withthe rapid development of computer, computervision technology is also making rapid progress. In this paper, deep neural network algorithm is used to improve the technology of computervision, improve the visual e...
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ISBN:
(纸本)9783031243660;9783031243677
Withthe rapid development of computer, computervision technology is also making rapid progress. In this paper, deep neural network algorithm is used to improve the technology of computervision, improve the visual effect, and at the same time, innovative algorithm structure, improve the identification of patternrecognition. computervision and patternrecognition is a very cutting edge technology that has given people very advanced tools for vision and recognition. At present, the technology can control more accurate image resolution and improve the ability of patternrecognition. this article mainly explains the process of using deep neural network algorithm to improve computervision and patternrecognition from the internal mechanism, and reveals the working principle and internal mechanism of computervision and patternrecognition technology application. Data analysis proves that the patternrecognition application established by deep neural network algorithm performs very well in the field of vision and patternrecognition.
Sorting of carrots is an important step after picking. Usually the sorting of carrots relies on human labor, which leads to a waste of manpower and time. We have developed a rolling carrot visual inspection device, wh...
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Despite the significant progress made by Transformer in image super-resolution tasks, it has not effectively utilized prior knowledge in the image frequency domain and differentiated the processing of high-frequency a...
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ISBN:
(纸本)9789819985517;9789819985524
Despite the significant progress made by Transformer in image super-resolution tasks, it has not effectively utilized prior knowledge in the image frequency domain and differentiated the processing of high-frequency and low-frequency information in the image. Previous studies on image super-resolution have shown that the high-frequency and low-frequency regions of the image exhibit distinct differences during the super-resolution process. In this paper, we propose a Discriminative Information Activation Super-Resolution Transformer (DIAST) to further improve the performance of Transformer in SISR tasks by discriminating high-frequency information from low-frequency information in images and discriminating cross-window information from inside-window information efficiently. Our results demonstrate that our method can further utilize the potential of the Transformer. the codes will be available at https://***/qyx1999/DIAST.
this paper proposes a radio frequency signal identification method based on deep neural network. First, this article abstracts the radio frequency signal into a plane diagram and converts the radio frequency signal id...
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Creating natural language descriptions or captions for images is a formidable task that requires a combination of computervision techniques to understand image content and natural language processing models to expres...
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To address the challenge of inadequate classification rate of the collected waste, the garbage classification imagerecognition model is designed based on machine vision technology, and after comparing the test effect...
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In the field of computervision and imageprocessing, texture provides critical visual clues about the composition of internal regions of an image. this paper proposes a novel texture image classification method using...
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the Wiener filter is used efficiently in removing noise from images, as it is used to remove Gaussian noise. However, its use causes the loss of edge details and blurring of images. the proposed image de-blurring usin...
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ISBN:
(纸本)9783031821554;9783031821561
the Wiener filter is used efficiently in removing noise from images, as it is used to remove Gaussian noise. However, its use causes the loss of edge details and blurring of images. the proposed image de-blurring using a combination of the Wiener filter and a sharpening filter is presented to solve the problem of blurry images. It retains or preserves edge content while reducing noise in an image. this enhancement process is performed by multiplying the frequency coefficients of the image by the weights of the sharpening filter. the inverse transform is then applied to obtain the de-blurred image. Different focus operators were used for testing the proposed algorithm. the experimental results showed that the proposed deblurring method produced good results compared withthe traditional de-blurring methods.
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