With the expansion of IoT application scenarios, the demand for edge IoT devices with integrated video analysis capabilities is gradually increasing. In remote areas where cellular base stations cannot reach, a low-co...
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The increasing spread of data and text documents such as articles, web pages, books, posts on social networks, etc. on the Internet, creates a fundamental challenge in various fields of text processing under the title...
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ISBN:
(纸本)9798350314557
The increasing spread of data and text documents such as articles, web pages, books, posts on social networks, etc. on the Internet, creates a fundamental challenge in various fields of text processing under the title of "automatic text summarization". Manual processing and summarization of large volumes of textual data is a very difficult, expensive, time-consuming, and impossible process for human users. Text summarization systems are divided into extractive and abstract categories. In the extractive summarization method, the final summary of a text document is extracted from the important sentences of the same document without any kind of change. In this method, it is possible to repeat a series of sentences repeatedly and interfere with pronouns. But in the abstract summarization method, the final summary of a textual document is extracted from the meaning of the sentences and words of the same document or other documents. Many of the performed works have used extraction methods or abstracts to summarize the collection of web documents, each of which has advantages and disadvantages in the results obtained in terms of similarity or size. In this research, by developing a crawler, extracting the popular text posts from the Instagram social network, suitable pre-processing, and combining the set of extractive and abstract algorithms, the researcher showed how to use each of the abstract algorithms. and used extraction as a supplement to increase the accuracy and accuracy of another algorithm. Observations made on 820 popular text posts on the Instagram social network show the accuracy (80%) of the proposed system.
The fundamental components of automated retinal blood vessel segmentation for eye disease screening systems are segmentation algorithms, retinal blood vessel datasets, classification algorithms, performance measure pa...
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Over the years there has been huge improvements in the performance of imageprocessingalgorithms due to increase in computation power of Devices as well as use of Neural Networks. This paper focuses on comparison of ...
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Transformer has been applied for polarimetric synthetic aperture radar (PolSAR) imageprocessing due to its ability to construct long-range dependency. However, Transformer lacks the learning of local spatial informat...
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The quality of image and videos plays a vital role in case of real-Time systems. images are captured without sufficient illumination, lead to low dynamic range and high propensity for generating high noise levels. The...
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With the rapid development of artificial intelligence technology, visual inspection and imageprocessingalgorithms have been continuously improved in accuracy and efficiency, and intelligent inspection systems based ...
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The proceedings contain 11 papers. The topics discussed include: a dynamic dictionary-based sparse reconstruction method for DOA estimation;method of weak communication signal detection and signal quality assessment a...
ISBN:
(纸本)9798400716171
The proceedings contain 11 papers. The topics discussed include: a dynamic dictionary-based sparse reconstruction method for DOA estimation;method of weak communication signal detection and signal quality assessment at low SNR;Non-coherent fusion detection method for distributed MIMO radar based on modified ordered statistics;wavelet based multiscale deep learning algorithms for arctic sea ice melting prediction;deception detection system with joint cross-attention;a transformer-based method for the registration of terahertz security images with visible light images;multi-resolution convolutional neural network for specific emitter identification;and EDV-HOP: enhanced distance vector hop localization for wireless sensor network.
To address issues of insufficient sensitivity and weak anti-noise characteristics in existing image sharpness evaluation algorithms, we propose a method combining local variance and gradient analysis. Traditional meth...
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Recently, vision model pre-training has evolved from relying on manually annotated datasets to leveraging large-scale, web-crawled image-text data. Despite these advances, there is no pre-training method that effectiv...
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