image acquisition in low-light environments often suffers from poor contrast, high noise, and loss of fine details, making effective enhancement challenging. Conventional enhancement methods frequently fail to balance...
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In this paper we present a system for person identification using dorsal hand veins pattern images. A simple approach is developed based on scale-invariant feature transform (SIFT) method for image features extraction...
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Sign languages play an important role to bridge the communication gap with hearing-impaired people. A lot of research is carried out to provide efficient, portable, and economical, tools, techniques, and products to m...
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The imageprocessing technology has been widely used in various field including video and image surveillance automatic capture the various application in image way representing. However, image process in different way...
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The work is devoted to the problem of moving objects extraction in a video sequence. The main feature of the problem considered is the presence of geometric transformations. The novelty of the proposed approach is con...
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Privacy violations are common in our technology-driven world, where almost everyone interacts with internet-connected electronic devices. To address this, cryptography has emerged, concealing data during transmission ...
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In order to obtain the low resolution(LR) image's detailed information, super resolution(SR) image reconstruction is essential. From 1D projections, we can reconstruct images in 2D and 3D. The LR images attained h...
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Multipliers play a role in various aspects of smart cities, which can be used in many applications like Traffic management, energy management and environmental management etc. The wide variety of applications of multi...
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wavelet transforms, a powerful mathematical tool, have been widely used in different domains, including signal and imageprocessing, to unravel intricate patterns, enhance data representation, and extract meaningful f...
ISBN:
(纸本)9798891760998
wavelet transforms, a powerful mathematical tool, have been widely used in different domains, including signal and imageprocessing, to unravel intricate patterns, enhance data representation, and extract meaningful features from data. Tangible results from their application suggest that wavelet transforms can be applied to NLP capturing a variety of linguistic and semantic properties. In this paper, we empirically leverage the application of Discrete wavelet Transforms (DWT) to word and sentence embeddings. We aim to showcase the capabilities of DWT in analyzing embedding representations at different levels of resolution and compressing them while maintaining their overall quality. We assess the effectiveness of DWT embeddings on semantic similarity tasks to show how DWT can be used to consolidate important semantic information in an embedding vector. We show the efficacy of the proposed paradigm using different embedding models, including large language models, on downstream tasks. Our results show that DWT can reduce the dimensionality of embeddings by 50-93% with almost no change in performance for semantic similarity tasks, while achieving superior accuracy in most downstream tasks. Our findings pave the way for applying DWT to improve NLP applications.
Approximate multipliers play a key role in reducing hardware complexity with minimum circuit components. By compensating the computational accuracy, approximate multipliers help in reducing the power consumption, proc...
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