Advanced object detection (OD) techniques have been widely studied in recent years and have been successfully applied in real-world applications. However, existing algorithms may struggle with nighttime image detectio...
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Power transformers are among the most important assets in the power transmission and distribution grid. However, they suffer from degradation and possible faults causing major electrical and financial losses. Partial ...
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Template matching is a well-known computer vision algorithm that involves scanning a template across various parts of an image. The template is correlated within this algorithm using a similarity or matching score, su...
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ISBN:
(数字)9798331509422
ISBN:
(纸本)9798331509439
Template matching is a well-known computer vision algorithm that involves scanning a template across various parts of an image. The template is correlated within this algorithm using a similarity or matching score, such as the Pearson correlation coefficient (PCC). A chieving a m ore a ccurate match necessitates searching many regions using the PCC metric, which is hindered by the Von Neumann Bottleneck, resulting in increased energy consumption and delays. Therefore, this paper proposes an energy-efficient, c omprehensive memristive in-memory computing architecture for template matching with its physical design, where the PCC computation unit sensor readout unit, DAC, demultiplexers, in-memory memristive computing array, ADC, running sum module, fixed point operation unit and comparator. The PCC equation is approximated, considering the limitations of the hardware characteristics and application requirements. The proposed approximated memristive in-memory based template-matching scheme demonstrates competitive performance compared to the Von Neumann system and achieves around 678× improvement in the power-delay product. Lastly, a threshold-based optimization strategy is suggested to reduce energy consumption in the application.
The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords:smaller,faster,and smarter.(1)Smaller:Devices are becoming more compact by integrating previously separated component...
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The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords:smaller,faster,and smarter.(1)Smaller:Devices are becoming more compact by integrating previously separated components such as sensors,memory,and processing *** a prime example,the transition from traditional sensory vision computing to in-sensor vision computing has shown clear benefits,such as simpler circuitry,lower power consumption,and less data redundancy.(2)Swifter:Owing to the nature of physics,smaller and more integrated devices can detect,process,and react to input more *** addition,the methods for sensing and processing optical information using various materials(such as oxide semiconductors)are evolving.(3)Smarter:Owing to these two main research directions,we can expect advanced applications such as adaptive vision sensors,collision sensors,and nociceptive *** review mainly focuses on the recent progress,working mechanisms,image pre-processing techniques,and advanced features of two types of neuromorphic vision sensors based on near-sensor and in-sensor vision computing methodologies.
Artificial Intelligence usually comprises a system that is composed of hardware and software. Machine learning is a subset of artificial intelligence (AI). The study discovered that the environment and contemporary te...
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Applications of sensor nodes in our daily lives are increasing. Sensor nodes can be embedded in textiles to monitor various environmental parameters or to measure biomarkers. Embedded nodes in fabrics can use wires as...
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ISBN:
(数字)9798350387568
ISBN:
(纸本)9798350387575
Applications of sensor nodes in our daily lives are increasing. Sensor nodes can be embedded in textiles to monitor various environmental parameters or to measure biomarkers. Embedded nodes in fabrics can use wires as means of communication. This approach, however, has drawbacks in terms of reliability, e.g. wire breaks, and discomfort that can arise in a large fabric network with multitudes of cables. Power-line communication (PLC) can mitigate these problems by using conductive planes instead of wires. However, the capacitance formed as a result of using two parallel plates and fabric in between attenuates the signal transmission between sensor nodes. Therefore, in order to compensate the attenuation effect of the conductive fabric which can be achieved by optimizing the hardware, we need to know the capacitance model of the conductive fabric. In our case it is necessary to know the capacitance model as a result of placing a cotton knit fabric between conductive meshes. In this work, we demonstrate that one can use the parallel plate capacitance model for estimating the capacitance of a cotton knit fabric placed between two conductive meshes.
The integration of Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing (QA) offers a promising approach to addressing energy management and load balancing challenges in modern power systems. This s...
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This paper proposes an intelligent dynamic modeling method for strip rolling process. Actuators of a cold rolling mill perform actions, including work roll bending, intermediate roll bending, and roll gap tilting, to ...
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This paper introduces a novel standard 3lead ECG monitoring system, designed for enhanced comfort in daily wear. The system utilizes innovative dry electrodes, seamlessly integrated into both underwear and shirts. The...
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We demonstrate a high performance back-end-of-line (BEOL) compatible tungsten (W)-doped In2O3 channel (IWO) dual gate (DG) field-effect transistor (FET) with ultra low-leakage current -15 A/μ m and high ION/IOFF rati...
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