Neural image compression employs deep neural networks and generative models to achieve impressive compression rates and reconstruction qualities compared to traditional signal-processing-based compression algorithms s...
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This research develops an algorithm for efficiently fusing multiple satellite images, addressing challenges like varying spatial resolutions, spectral bands, radiometric differences, and geometric distortions. Objecti...
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This paper presents a study on the multilayer bottleneck autoencoder applied for thumbnail color image compression task using quaternionic neural nets (QNN). Existing state-of-the-art real-valued autoencoder architect...
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image captioning consists of describing the image content with words and sentences. This task can be seen as the junction of Natural Language processing (NLP) and computer vision. Describing the visual content of imag...
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ISBN:
(数字)9783031298608
ISBN:
(纸本)9783031298592;9783031298608
image captioning consists of describing the image content with words and sentences. This task can be seen as the junction of Natural Language processing (NLP) and computer vision. Describing the visual content of images remains a difficult task because it involves both image and text processingalgorithms. To better understand this new research area, the main objective of this paper is to present an image captioning comprehensive study. In this work, the most used techniques, datasets, and evaluation metrics will be presented and discussed. At the end, a comparative study between an attention model and a transformer model for image captioning will be presented.
This paper presents a novel comparative study between two prominent compressed sensing algorithms - Orthogonal Matching Pursuit (OMP) and Iterative Hard Thresholding (IHT) - within the context of digital holography, s...
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ISBN:
(纸本)9781510673151;9781510673144
This paper presents a novel comparative study between two prominent compressed sensing algorithms - Orthogonal Matching Pursuit (OMP) and Iterative Hard Thresholding (IHT) - within the context of digital holography, specifically focusing on their efficacy in handling phase discontinuities. Previous research has predominantly centered on Gibbs ringing artifacts in image reconstruction and their mitigation. However, the aspect of phase discontinuities, which are critical in holographic imaging, has not been extensively explored. Our study implement both OMP and IHT algorithms in a simulated digital holographic environment, where phase discontinuities are inherent due to the nature of holographic imaging. We analyze how these algorithms perform in the presence of phase discontinuities. We quantitatively analyze the performance of each algorithm in handling phase discontinuities. Additionally, our study delves into the computational efficiency of both algorithms, considering their practical applicability in real-time holographic imaging systems. The results of our comparative analysis provide insights into the advantages and limitations of OMP and IHT in the context of phase discontinuities. Our findings have significant implications for advancing digital holography, particularly in applications requiring precise phase information, such as medical imaging, microscopy, and non-destructive testing.
The article describes imageprocessing, where a comparison of selected image segmentation algorithms for counting the number of objects in an image was performed. The comparison was performed on a real example of phot...
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In spaceborne SAR imageprocessing, focusing algorithms are applied with a uniform altitude throughout the observation area. The uniform altitude assumption shows good performance in most spaceborne SAR systems. Howev...
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The study focuses on the utilization of remote sensing data to analyze and detect deforestation patterns, with an emphasis on the extraction of key parameters such as vegetation cover change, forest loss, and land use...
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This project aims to develop a solar powered auto irrigation system that incorporates imageprocessing techniques to monitor and maintain the health of the plants. The system utilizes solar energy to power the irrigat...
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This work presents a new approach to crop quality monitoring that makes use of deep learning vision algorithms and a Single Board Computer (SBC). Our approach consists of a multi-step imageprocessing pipeline, wherei...
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ISBN:
(纸本)9798350367393;9798350367386
This work presents a new approach to crop quality monitoring that makes use of deep learning vision algorithms and a Single Board Computer (SBC). Our approach consists of a multi-step imageprocessing pipeline, wherein the ROI (Region of Interest) is first identified using a specialised Vegetation determination procedure (NDVI). Furthermore, geo-coordinates enabling accurate geospatial mapping of crop quality measurements. A 5-layer CNN classifier, as well as deep learning models for leaf classification and optimised picture filtering, augmentation, and segmentation, come next. The system's real-time capabilities were assessed using an Nvidia Jetson Nano Developer kit.
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