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检索条件"任意字段=Conference on Signal and Data Processing of Small Targets 1994"

共 765 条记录，以下是11-20 订阅

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MKD-YOLO: Multi-Scale and Knowledge-Distilling YOLO for Efficient PPE Compliance Detection

MKD-YOLO: Multi-Scale and Knowledge-Distilling YOLO for Effi...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Juntao Zan Yang Fang Qilie Liu Uswah Khairuddin Yan Li Kaiwei Sun School of Communications and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecommunications Chongqing China Malaysia-Japan International Institute of Technology University of Technology Malaysia Kuala Lumpur Malaysia Department of Electrical and Computer Engineering Inha University Incheon South Korea Key Laboratory of Data Engineering and Visual Computing Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

YOLO-based models are widely used for personal protective equipment (PPE) compliance detection due to their excellent detection performance and efficiency. However, most YOLO models are not competent for detection tasks in complex industrial scenarios such as remote surveillance and extremely small targets. In addition, there is a lack of effective model lightweighting and knowledge transfer approaches for industrial deployment. To this end, this paper proposes a Multi-scale and Knowledge-Distilling YOLO (MKD-YOLO) based on YOLOv8n for efficient PPE compliance detection. Specifically, in backbone stage, we design an Efficient Multi-Scale Enhanced Convolution (C2f-EMSEC) module and Large Spatial Pyramid Pooling-Fast (LSPPF) module for multi-scale and global-contextual feature learning as well as reducing model complexity. Then, in neck stage, a refined Bidirectional feature Pyramid Network (BPNet) is designated to capture fine-grained details for extremely small object detection. Moreover, we apply channel-wise knowledge distillation to facilitate model lightweighting and domain-specific knowledge transfer learning. Experiments on our proposed dataset and public datasets show that the proposed MKD-YOLO achieves a new state-of-the-art (SOTA) detection performance and efficiency for practical PPE compliance detection tasks. Codes and the dataset are available at https://***/z1Zjt/MKD-YOLO.

关键词： Personal protective equipment YOLO Representation learning Convolution Surveillance Speech enhancement Feature extraction Neck Kernel Knowledge transfer

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SUPER NONCOHERENT INTEGRATION - ANALYSIS OF PERFORMANCE

SUPER NONCOHERENT INTEGRATION - ANALYSIS OF PERFORMANCE

引用

conference on signal and data processing of small targets 1994

作者： DAUM, F RAYTHEON CO WAYLANDMA 01778

ISBN: (纸本)0819415391

This paper analyzes a new method to detect targets. The new method, called `super noncoherent integration' (SNCI), can improve overall detection performance by typically 5 dB to 10 dB relative to conventional noncoherent integration. A simple back-of-the-envelope formula is derived which quantifies the performance improvement of SNCI. Conventional noncoherent integration (CNCI) uses only amplitude measurements to distinguish targets from noise or clutter. In contrast, SNCI uses amplitude data in addition to: monopulse data, quadrature monopulse data, range and Doppler data over a sequence of N transmitted radar waveforms.

关键词： signal to noise ratio Doppler effect Radar Target detection Sensors Filtering (signal processing) Detection and tracking algorithms Error analysis Infrared sensors signal detection

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MULTIRESOLUTIONAL TARGET TRACKING

MULTIRESOLUTIONAL TARGET TRACKING

引用

conference on signal and data processing of small targets 1994

作者： HONG, L WRIGHT STATE UNIV DEPT ELECT ENGNDAYTONOH 45435

ISBN: (纸本)0819415391

A framework of multiresolutional target tracking is established in this paper. The wavelet transform is employed in constructing multiresolutional data and model structures. Multiresolutional tracking is performed over the multiresolutional data and model structures in a top-down fashion. The main advantages of multiresolutional target tracking include: computational efficiency, performance robustness and algorithm flexibility.

关键词： Detection and tracking algorithms data modeling Wavelet transforms data processing Optical filters data acquisition Distance measurement Electronic filtering Discrete wavelet transforms signal processing

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MAXIMIZATION OF RADAR SCAN FRAME TIME FOR TRACKING A MANEUVERING TARGET

MAXIMIZATION OF RADAR SCAN FRAME TIME FOR TRACKING A MANEUVE...

引用

conference on signal and data processing of small targets 1994

作者： MALAKIAN, K MARTIN MARIETTA GOVT ELECTR SYST MOORESTOWNNJ 08057

Analytic expressions are derived based on tracker characteristics that determine the maximum scan frame time required to track a maneuvering target. The tracker characteristics chosen are: filter gain, measurement cor... 详细信息

ISBN: (纸本)0819415391

关键词： Radar Filtering (signal processing) Fourier transforms Electronic filtering Image filtering

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COMPARISON OF POINT-SOURCE ALGORITHMS FOR OPTIMUM ACQUISITION RANGE OF ELECTROOPTICAL SENSOR

COMPARISON OF POINT-SOURCE ALGORITHMS FOR OPTIMUM ACQUISITIO...

引用

conference on signal and data processing of small targets 1994

作者： JHA, US ROCKWELL INT CORP DIV AUTONET ELECTR SYSTANAHEIMCA 92803

ISBN: (纸本)0819415391

This paper examines a special class of signal processing technique called Minimum Variance Deconvolution (MVD) method and compares it with the commonly used Matched filtering and Wiener filtering based deconvolution processing in point source acquisition signal processing applications for Electro-Optical sensors. A step by step development of the batch and recursive MVD algorithm including comparison with the competing methods are presented in this paper.

关键词： Filtering (signal processing) Electronic filtering signal to noise ratio signal processing Deconvolution Digital filtering Electro optical sensors Algorithm development Electro optical modeling Error analysis

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DIM POINT TARGET DETECTING FROM IMAGE SEQUENCES

DIM POINT TARGET DETECTING FROM IMAGE SEQUENCES

引用

conference on signal and data processing of small targets 1994

作者： LI, ZY SHEN, ZK NATL UNIV DEF TECHNOL DEPT EECHANGSHAPEOPLES R CHINA

ISBN: (纸本)0819415391

The technique of detecting and tracking of a moving point target is space-based background with low SNR is analyzed in this paper. An efficient method for detecting low speed targets is presented. The method simply uses multi-frame accumulating as the main operation in improving the output SNR. And it introduces candidate target records for target matching and recognition. The method is easy for hardware implementation that meets the demands of real time processing and low power consumption.

关键词： Target detection Target recognition signal to noise ratio Image processing Image storage Sensors Binary data Dysprosium Image sensors Computer programming

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TOWARD THE INTEGRATION OF TRACKING AND signal-processing FOR PHASED-ARRAY RADAR

TOWARD THE INTEGRATION OF TRACKING AND SIGNAL-PROCESSING FOR...

引用

conference on signal and data processing of small targets 1994

作者： BLAIR, WD USN CTR SURFACE WARFAREDAHLGREN DIVDEPT RES & TECHNOLDAHLGRENVA 22448

ISBN: (纸本)0819415391

Classically, sensor signal processing and data processing (i.e., tracking) have been performed separately with very little interaction between the two functions. Furthermore, the signal processing and tracking algorithms are often designed separately. This paper discusses some concepts for integrating the signal processing and tracking functions for a phase array radar. Since phased array radars provide a rapid beam steering capability, proper control of the radar beam has the potential for significantly improving the tracking of multiple maneuvering targets. However, when the signal processing is accomplished separately from the tracking, optimizing the detection thresholds for targets with fluctuating radar cross sections, resolving multiple targets, and reducing the errors due to multipath and glint must be accomplished over a single radar dwell period. Integrating the signal processing with the tracking will allow many of these issues to be addressed over multiple radar dwells. The issues associated with integrating the signal processing and tracking functions are discussed with respect to tracking and data association, revisit time and waveform energy calculations, and waveform selection. The waveform selection is discussed relative to four specific examples that include a fluctuating radar cross section from an extended target, two closely spaced targets, a splitting target, and a target in the presence of radar multipath.

关键词： Radar signal processing Target detection Detection and tracking algorithms Filtering (signal processing) signal to noise ratio Phased arrays Radar signal processing Electronic filtering signal detection

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TRACKING WITH FUSED NONCOINCIDENT MEASUREMENTS

TRACKING WITH FUSED NONCOINCIDENT MEASUREMENTS

引用

conference on signal and data processing of small targets 1994

作者： RAGO, C WILLETT, P BARSHALOM, Y UNIV CONNECTICUT STORRSCT 06269

ISBN: (纸本)0819415391

If members of a suite of sensors from which fusion is to be carried out are not co-located, it is unreasonable to assume that they share a common resolution cell grid; this is generally ignored in the data fusion community. In this paper we explore the effects of such `noncoincidence', and we find that what at first seems to be a problem can in fact be exploited. The idea is that a target is known to be confined to an intersection of overlapping resolution cells, and this overlap is generally small.

关键词： Sensors Radar Error analysis Stochastic processes data fusion Filtering (signal processing) Monte Carlo methods Target detection Optical resolution Sensor fusion

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THE APPLICATION OF DIFFERENCE METHOD TO DIM POINT TARGET DETECTION IN INFRARED IMAGES

THE APPLICATION OF DIFFERENCE METHOD TO DIM POINT TARGET DET...

引用

conference on signal and data processing of small targets 1994

作者： YANG, WP SHEN, ZK LI, ZY NATL UNIV DEF TECH DEPT ELEC ENGHUNAN 410073PEOPLES R CHINA

ISBN: (纸本)0819415391

This paper deals with the detection of dim point targets in infrared images. Dim point targets detection is always a difficulty in information processing. Researchers have proposed many effective methods in this aspect, here this paper no longer mentions them but will introduce a new method. Whereas difference method has obtained good result in one dimensional signal processing this paper manages to apply it to two dimensional signal processing, that is to say, dim point targets detection in infrared images of low SNR. The image background is color noise, and its column correlation is strong. So, ordinary methods probably lose the true targets because of the strong color noise, but unlike them, difference method can overcome this shortcoming, it can eliminate correlation noise and enhance useful information, finally pick out the probable targets from noise background. In the paper, the method was given a more extensive acount. In order to improve the detection effect, we utilized prefilter, The prefilter is realized by the alpha filter. Because the same targets have same location in more than three frames, using alpha filter can utilize the information of adjacent frames, increase the SNR of the raw data and reduce the noise of the images. © 1994 SPIE. All rights reserved.

关键词： signal to noise ratio

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MULTICHANNEL, TIME-DEPENDENT WHITENING OF NON-GAUSSIAN data FOR WEAK-signal IMAGE-processing

MULTICHANNEL, TIME-DEPENDENT WHITENING OF NON-GAUSSIAN DATA ...

引用

conference on signal and data processing of small targets 1994

作者： SILVA, DM WARREN, RE LITTLE, JG SRI INT MENLO PKCA 94025

ISBN: (纸本)0819415391

We present an integrated, theoretically self-consistent approach to the optimal processing of non-Gaussian data for weak-signal image processing in multichannel correlated clutter backgrounds. Our approach combines linear predictive filtering with locally optimal detection theory to perform both intra- and interchannel whitening and soft editing within the context of Neyman-Pearson likelihood ratio processing. Whitening coefficients are estimated from a multichannel formulation of the Yule-Walker equations. Soft editing is performed by way of a nonlinear operator computed from the multichannel joint density of whitened residuals, which, in the Gaussian limit, is shown to reduce to a channel-dependent conditional mean subtraction. We assume the signal to be deterministic. In addition, we also assume that non-Gaussian departures in the data are limited in both space and time. processing results are presented for both simulated and real data and are compared with standard Fourier-based approaches.

关键词： Sensors data modeling Image processing signal detection signal to noise ratio signal processing Autoregressive models data processing Nonlinear filtering Linear filtering

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