We introduce a real-time undersampled dynamic MRI algorithm, termed FewShot-AltGDmin-MRI, that is generalizable: works for many different applications and sampling trajectories without any application-specific paramet...
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ISBN:
(数字)9798350368741
ISBN:
(纸本)9798350368758
We introduce a real-time undersampled dynamic MRI algorithm, termed FewShot-AltGDmin-MRI, that is generalizable: works for many different applications and sampling trajectories without any application-specific parameter tuning. FS-AGM-MRI operates in real-time after processing the first short mini-batch, i.e., it can provide a reconstruction of each new image frame as soon as the MRI scan data for that frame arrives. It also provides a second set of improved quality reconstructions after a short delay. We compare our algorithm against many state of the art batch MRI algorithms, including Deep Learning (DL) based ones, on 17 different retrospectively undersampled datasets and two prospective datasets. FS-AGM-MRI is the only approach that provides accurate recovery for all datasets while also being one of the fastest.
The primary objective of this study was to address the critical challenge of obtaining accurate information regarding the spatial distribution and classification of crops in agricultural areas. The aim was to enhance ...
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A blurred image is an image that has undergone a blurring or smoothing effect, resulting in a loss of sharpness and clarity. Blurring is a technique used in imageprocessing to reduce noise, remove unwanted details, o...
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ISBN:
(数字)9798331534967
ISBN:
(纸本)9798331534974
A blurred image is an image that has undergone a blurring or smoothing effect, resulting in a loss of sharpness and clarity. Blurring is a technique used in imageprocessing to reduce noise, remove unwanted details, or create a visual effect. It involves averaging or blending neighboring pixels to create a smoother appearance. The specific processing techniques and algorithms used will depend on the nature and extent of the blur, the intended outcome, and the available software or programming tools. It's important to experiment with different methods and parameters to achieve the desired result. IoT (Internet of Things) can be used in imageprocessing in several ways to enhance functionality, efficiency, and data processing capabilities enhances imageprocessing by enabling real-time analysis, edge computing capabilities, integration with other IoT devices, and remote monitoring and control. These advancements facilitate applications such as object detection, image recognition, and real-time decision-making, contributing to more efficient and intelligent systems in various domains. Here is a proposed model for blurred imageprocessing with IoT. This proposed model demonstrates the integration of IoT devices, imageprocessing techniques, and cloud-based analytics to address the challenges of blurred imageprocessing. It combines edge processing for real-time analysis and cloud-based processing for more complex algorithms, enabling efficient and intelligent imageprocessing applications in various domains.
Plants can be classified based on various classification methods such as cell, genetic and serum etc. It's difficult for an individual to explore the various classification methods and it's practically not fea...
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In this paper, we propose an image contrast enhancement mechanism by analysing the dominant colour component of every contributory pixel. The contrast enhancement is performed on the regions having similar dominating ...
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ISBN:
(数字)9798350367157
ISBN:
(纸本)9798350367164
In this paper, we propose an image contrast enhancement mechanism by analysing the dominant colour component of every contributory pixel. The contrast enhancement is performed on the regions having similar dominating colour components by employing local histogram equalization. The process ensures the increment of the colour purity by preserving the level of brightness which is a major drawback of histogram equalization-based methods. The proposed method provides satisfactory results without any learning mechanism applied in the system which reduces the execution time of the process as well. The proposed algorithm is formulated, experimented and tested on a large set of standard colour images, in RGB format, collected from various databases. We compare the proposed method with both standalone and learning based image enhancement algorithms from the literature. The comparative analysis establishes the efficacy of the proposed method.
This paper is based on the application of lossless compression algorithms in image compression, aiming to solve problems such as insufficient storage space, low transmission efficiency, and heavy data processing burde...
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ISBN:
(数字)9798350350760
ISBN:
(纸本)9798350350777
This paper is based on the application of lossless compression algorithms in image compression, aiming to solve problems such as insufficient storage space, low transmission efficiency, and heavy data processing burden. In order to optimize the image lossless compression algorithm, a combination of Huffman encoding and LZW compression algorithm is proposed. The implementation process and advantages and disadvantages of the two are compared, and the compression ratio and encoding efficiency of image lossless compression technology are discussed. We need to optimize decoding speed, image quality, and other aspects to improve overall image lossless compression capability. By applying Huffman encoding and LZW compression algorithms to images separately, the results show that Huffman encoding can dynamically construct the optimal encoding based on the frequency of characters appearing in image data, while LZW technology is good at utilizing repeated patterns and contextual information in image data to further improve compression efficiency by establishing dictionaries. The complementary advantages of the two can further improve the lossless compression ability of images.
In comparison to other types of cancer, lung cancer has the highest fatality rate, making it one of the most dangerous illnesses in the world. In India, there are over 70,000 new cases recorded each year, which demons...
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Autonomous driving systems operate in highly complex environments, necessitating real-time, balanced decisionmaking across multiple objectives such as safety, efficiency, and passenger comfort. This study introduces R...
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ISBN:
(数字)9798350355413
ISBN:
(纸本)9798350355420
Autonomous driving systems operate in highly complex environments, necessitating real-time, balanced decisionmaking across multiple objectives such as safety, efficiency, and passenger comfort. This study introduces RecOpt, a novel framework that combines recommender algorithms with advanced optimization techniques to enhance multi-objective optimization (MOO) in decision-making. RecOpt tackles the challenges of large-scale mixed-integer MOO by identifying and restructuring key decision variables, thereby reducing the optimization scale and increasing efficiency. By integrating recall and finesorting technologies inherent in recommender systems, RecOpt efficiently screens and selects optimal solutions, surpassing the speed and scalability limitations of traditional MOO methods. Experiments utilizing the NGSIM dataset validate RecOpt’s efficacy in balancing safety, comfort, and efficiency, minimizing decision-making latency, and adapting to dynamic environments. Furthermore, RecOpt offers data-driven insights into explainable decision-making, providing a robust and transparent model for autonomous vehicle decision processes.
Autonomous vehicles require real-time imageprocessing to improve their capabilities by allowing them to understand and respond appropriately to their environment. This paper examines the present state of real-time im...
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ISBN:
(数字)9798350374957
ISBN:
(纸本)9798350374964
Autonomous vehicles require real-time imageprocessing to improve their capabilities by allowing them to understand and respond appropriately to their environment. This paper examines the present state of real-time imageprocessing for self-driving vehicles, including the techniques employed, challenges, and advancements. This article investigates methods such as semantic segmentation, object recognition, categorization, and depth estimation, with an emphasis on enhancing vehicle perception, navigation, and decision-making. The article delves into the implementations of significant algorithms on embedded platforms, their computational efficiency, and their deployment in real-world scenarios. In conclusion, the report investigates prospective avenues for additional research to improve the reliability and efficiency of the real-time imageprocessingsystems of autonomous automobiles.
The agricultural landscape is evolving, demanding innovative solutions to enhance productivity while ensuring the welfare of livestock. Farmguard introduces an advanced Automated Animal Detection and Monitoring System...
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ISBN:
(数字)9798350365092
ISBN:
(纸本)9798350365108
The agricultural landscape is evolving, demanding innovative solutions to enhance productivity while ensuring the welfare of livestock. Farmguard introduces an advanced Automated Animal Detection and Monitoring System designed to revolutionize traditional farm management practices. Leveraging cutting-edge sensor technology, computer vision, and machine learning algorithms, Farmguard offers real-time, non-invasive monitoring of animal behavior, health, and movement within farm premises. This system operates seamlessly, utilizing a network of strategically placed sensors and cameras to track and identify individual animals. Through sophisticated imageprocessing and AI-powered algorithms. This technology aims to minimize conflicts by providing early warnings about animal intrusion, enabling timely intervention strategies. By leveraging Arduino's capabilities and imageprocessing techniques.
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