imageprocessing has become one of the popular neuromorphic computing applications in recent years. Most of the application areas require an efficient and realtimeimageprocessing system. Memristor is a useful memor...
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ISBN:
(数字)9798331501488
ISBN:
(纸本)9798331501495
imageprocessing has become one of the popular neuromorphic computing applications in recent years. Most of the application areas require an efficient and realtimeimageprocessing system. Memristor is a useful memory device which plays an important role to design an imageprocessing system and realization of hardware design. Due to the non-volatile nature of memory and less power consumption, Memristor has a huge application in the field of imageprocessing. Being a memory device, Memristor can preserve data and parameters during processingtime and reducing the need for data transfer as well as storage. In this research, Memristor in the form of CNN architecture will store the image extracted data where pixel image is given as an input and voltage pulses are generated according to the pixel value. The voltage pulses are then applied as input to the Memristor crossbars and compared with a certain threshold voltage above which an output neuron responds. The above mention system is trained for image recognition applications in realtime scenarios. The realtimeimageprocessing based Memristor system can have huge application areas such as medical imaging, security, computer vision and robotics.
Quantum experiments are an essential part of research into innovative quantum technologies that protect us, determine time, or help us navigate every day [1]. Such platforms include quantum computers, quantum cryptogr...
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Nowadays, many applications based on imageprocessing methods are deployed to bring convenience to use due to its outstanding superior features. This paper proposes an imageprocessing-based method for determining the...
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The proceedings contain 3 papers. The topics discussed include: real-time implementation of an artificial stereo audio extension method;noise model analysis for sensor arrays;and remarks on four-dimensional probabilis...
ISBN:
(纸本)9781479977697
The proceedings contain 3 papers. The topics discussed include: real-time implementation of an artificial stereo audio extension method;noise model analysis for sensor arrays;and remarks on four-dimensional probabilistic finite automata.
The proceedings contain 26 papers. The topics discussed include: building extraction from high-resolution remote sensing image based on improved ResUNet network;a visual based algorithm for measuring the speed of scra...
ISBN:
(纸本)9798400718090
The proceedings contain 26 papers. The topics discussed include: building extraction from high-resolution remote sensing image based on improved ResUNet network;a visual based algorithm for measuring the speed of scrap metal vibration feeding;semantic segmentation for virtual-real fusion data processing in nonferrous metal process industry;an evaluation method based on fuzzy model for the autonomous and controllable of the spacecraft component production;discrete-time physics-informed neural networks for two-phase flow interface capturing;comprehensive review: advancing cognitive computing through theory of mind integration and deep learning in artificial intelligence;and kinematics behaviors evaluation of a naval ship survival training simulation system in case of longitudinal shaking.
With the advancements in artificial intelligence (AI) and unmanned aerial vehicle (UAV) inspection technologies, enhancing the automated accuracy of UAV inspection images and ensuring stable power grid operation has b...
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The accuracy and real-time performance of existing traffic sign recognition methods in complex environments need to be improved. This study aims to propose an efficient traffic sign recognition solution based on machi...
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ISBN:
(数字)9798331529246
ISBN:
(纸本)9798331529253
The accuracy and real-time performance of existing traffic sign recognition methods in complex environments need to be improved. This study aims to propose an efficient traffic sign recognition solution based on machine vision imageprocessing technology. First, a high-definition camera is used to collect road scene images in realtime and preprocess them, including converting the image into a grayscale image, using Gaussian filtering to remove noise, and using the Canny edge detection algorithm to extract edge information. Next, morphological operations such as dilation and erosion are used to further enhance the features of traffic signs. The recognition rate of this method on the test set reached 98.9%, and the processingtime of 120 codes was 50 milliseconds, which met the requirements of real-time recognition. The application of machine vision-based imageprocessing technology in traffic sign recognition effectively improves the recognition accuracy.
Pre-trained text-to-image (T2I) synthesis diffusion models (DM) have shown remarkable capabilities in generating diverse images. However, they struggle to satisfy the user's requirements due to (i) text's inhe...
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This study develops a scalable, effective, and user-friendly solution to tackle the problem of real-time object detection in photos. The suggested approach makes use of YOLOv5 (You Only Look Once version 5) for deep l...
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