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192 results on '"Meng, Zhichao"'

1. Comprehensive Performance Evaluation of YOLOv10, YOLOv9 and YOLOv8 on Detecting and Counting Fruitlet in Complex Orchard Environments

Author

Sapkota, Ranjan, Meng, Zhichao, Churuvija, Martin, Du, Xiaoqiang, Ma, Zenghong, and Karkee, Manoj

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

This study performed an extensive evaluation of the performances of all configurations of YOLOv8, YOLOv9, and YOLOv10 object detection algorithms for fruitlet (of green fruit) detection in commercial orchards. Additionally, this research performed and validated in-field counting of fruitlets using an iPhone and machine vision sensors in 5 different apple varieties (Scifresh, Scilate, Honeycrisp, Cosmic crisp & Golden delicious). This comprehensive investigation of total 17 different configurations (5 for YOLOv8, 6 for YOLOv9 and 6 for YOLOv10) revealed that YOLOv9 outperforms YOLOv10 and YOLOv8 in terms of mAP@50, while YOLOv10x outperformed all 17 configurations tested in terms of precision and recall. Specifically, YOLOv9 Gelan-e achieved the highest mAP@50 of 0.935, outperforming YOLOv10n's 0.921 and YOLOv8s's 0.924. In terms of precision, YOLOv10x achieved the highest precision of 0.908, indicating superior object identification accuracy compared to other configurations tested (e.g. YOLOv9 Gelan-c with a precision of 0.903 and YOLOv8m with 0.897. In terms of recall, YOLOv10s achieved the highest in its series (0.872), while YOLOv9 Gelan m performed the best among YOLOv9 configurations (0.899), and YOLOv8n performed the best among the YOLOv8 configurations (0.883). Meanwhile, three configurations of YOLOv10: YOLOv10b, YOLOv10l, and YOLOv10x achieved superior post-processing speeds of 1.5 milliseconds, outperforming all other configurations within the YOLOv9 and YOLOv8 families. Specifically, YOLOv9 Gelan-e recorded a post-processing speed of 1.9 milliseconds, and YOLOv8m achieved 2.1 milliseconds. Furthermore, YOLOv8n exhibited the highest inference speed among all configurations tested, achieving a processing time of 4.1 milliseconds while YOLOv9 Gelan-t and YOLOv10n also demonstrated comparatively slower inference speeds of 9.3 ms and 5.5 ms, respectively., Comment: 14 figures, 2 tables

Published
2024

34. Forward-looking Multi-channel SAR Adaptive Identification to Suppress Deception Jamming

Author

MENG Zhichao, LU Jingyue, and ZHANG Lei

Subjects
Forward-Looking Multi-Channel SAR (FLMC SAR), Azimuth ADaptive Beam Forming (AADBF), Deception jamming, Interference suppression, Electricity and magnetism, QC501-766
Abstract

Forward-looking multi-channel SAR imaging suffers from ambiguity regarding left and right echoes. To deblur the imaging process, spatial resources must be used, which make the imaging process more complex than the general side-looking SAR. In complex electromagnetic environments, it is very difficult to obtain forward-looking SAR images without interference or ambiguity. In this paper, we present an adaptive discriminant suppression algorithm that addresses deception jamming based on Azimuth ADaptive Beam Forming (AADBF). First, we use the AADBF technique to cancel the multi-channel received echo signal and retain the deception jamming samples. Then, we use the threshold detection method to identify the pixel location of the deception jamming on high-resolution SAR images. Finally, we apply adaptive spatial filtering to pixels with interference to achieve anti-deception jamming. Simulation results show that this method can effectively identify and suppress deception jamming, while realizing forward-looking SAR non-interference focusing imaging.

Published
2019
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37. FL-PFA: A Polar Format Algorithm for Wide-Beam Forward-Looking SAR Imaging Integrating Spatial-Variant Motion Compensation

Author

Meng, Zhichao, Zhang, Lei, Lu, Jingyue, and Wang, Xinshuo

Abstract

Multichannel forward-looking synthetic aperture radar (FLSAR) imaging presents challenges due to spatiotemporal coupling, especially in wide-beam scenarios. This article introduces a new polar format algorithm (PFA) called the forward-looking polar format algorithm (FL-PFA) for wide-beam FLSAR imaging. The proposed algorithm utilizes a time-space–time hybrid scheme to address the spatiotemporal coupling, matching the spatiotemporal structure of FLSAR echoes. Furthermore, the scheme combines spatial-variant motion compensation (MOCO) and polar format imaging, resulting in an efficient processing flow. For spatial-variant MOCO, this article introduces an adaptive subaperture topography- and aperture-dependent (ASATA) algorithm, offering the advantage of balancing compensation accuracy and efficiency using adaptive optimal subapertures. Subsequently, a novel PFA is proposed to obtain a focused FLSAR image. In the PFA, the azimuth angle wavenumber considers both the spatial-variant quadratic phase and residual motion errors, aligning with the spatial-variant Doppler modulation rate characteristic of FLSAR. By resampling the azimuth angle wavenumber, a well-focused FLSAR image on the polar coordinate grid and more accurate MOCO can be achieved simultaneously. Finally, extensive experiments using simulated and actual synthetic aperture radar (SAR) data demonstrate the superiority of FL-PFA.

Published
2024
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39. Cellulose in situ formation of three primary nanoparticles for polymer scalable colors.

Author

Zhang, Yang, Xu, Zhiqiang, Meng, Zhichao, Shi, Shan, and Sui, Guoxin

Subjects
ARTIFICIAL skin, CELLULOSE, ELECTRONIC packaging, VISIBLE spectra, EPOXY resins, POLYMERS, COLORS
Abstract

Polymer coloration technology has been receiving increasing attention in different fields including electronic packaging, artificial skin and 3D printing. Herein, we report a new strategy utilizing three primary nanocomposites (cellulose@Fe3O4, cellulose@FeOOH and cellulose@PB) as unique coloring components for scalable colored polymer-based composites. Taking the epoxy resin as polymer matrix for example, the as-made polymer-based composites present different colors, including red/yellow/blue colors and many spectral colors achieved by mixing the three primary nanocomposites. The nanocomposites act not only as the primary nanopigments, but also as the connected bridge to tightly stick polymer matrix through strong chemical bonding, respectively. In addition, the colored polymer-based composites show excellent opacity and UV protection. Our work offers a facile coloration approach for arbitrary colors over the whole visible spectra by mixing three primary nanocomposites at different ratios in the polymer field. With bright, uniform, and ratio-dependent color, we showcase three typical polymers to demonstrate the versatility of coloring strategy. We have developed a simple strategy to fabricate cellulose in situ deposited three primary nanocomposites. Taking the polymer matrix for example, arbitrary color can be created by mixing them into polymer at different ratios over the whole visible spectra by dispersing three primary nanocomposites. [ABSTRACT FROM AUTHOR]

Published
2023
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