scholarly journals Research on Subway Pedestrian Detection Algorithm Based on Big Data Cleaning Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zhuoyang Lyu
Keyword(s):  
Data Cleaning ◽  
Pedestrian Detection ◽  
Detection Algorithm ◽  
Motion Blur ◽  
Cleaning Process ◽  
Detection Model ◽  
Subway Stations ◽  
Cleaning Technology ◽  
Blurred Images

The pedestrian detection model has a high requirement on the quality of the dataset. Concerning this problem, this paper uses data cleaning technology to improve the quality of the dataset, so as to improve the performance of the pedestrian detection model. The dataset used in this paper is obtained from subway stations in Beijing and Nanjing. The data images’ quality is subject to motion blur, uneven illumination, and other noisy factors. Therefore, data cleaning is very important for this paper. The data cleaning process in this paper is divided into two parts: detection and correction. First, the whole dataset goes through blur detection, and the severely blurred images are filtered as the difficult samples. Then, the image is sent to DeblurGAN for deblur processing. 2D gamma function adaptive illumination correction algorithm is used to correct the subway pedestrian image. Then, the processed data is sent to the pedestrian detection model. Under different data cleaning datasets, through the analysis of the detection results, it is proved that the data cleaning process significantly improves the detection model’s performance.

scholarly journals Research on Lightweight Infrared Pedestrian Detection Model Algorithm for Embedded Platform

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Zhaoli Wu ◽  
Xin Wang ◽  
Chao Chen
Keyword(s):  
Real Time ◽  
Target Detection ◽  
Pedestrian Detection ◽  
Infrared Image ◽  
Far Infrared ◽  
Detection Algorithm ◽  
Model Parameters ◽  
Detection Accuracy ◽  
Detection Model ◽  
Embedded Platform

Due to the limitation of energy consumption and power consumption, the embedded platform cannot meet the real-time requirements of the far-infrared image pedestrian detection algorithm. To solve this problem, this paper proposes a new real-time infrared pedestrian detection algorithm (RepVGG-YOLOv4, Rep-YOLO), which uses RepVGG to reconstruct the YOLOv4 backbone network, reduces the amount of model parameters and calculations, and improves the speed of target detection; using space spatial pyramid pooling (SPP) obtains different receptive field information to improve the accuracy of model detection; using the channel pruning compression method reduces redundant parameters, model size, and computational complexity. The experimental results show that compared with the YOLOv4 target detection algorithm, the Rep-YOLO algorithm reduces the model volume by 90%, the floating-point calculation is reduced by 93.4%, the reasoning speed is increased by 4 times, and the model detection accuracy after compression reaches 93.25%.

Study on the Effect of Cleaning Technology of Fresh Tea Leaves on the Quality of Green Tea

2020 ◽  
Vol 984 ◽  
pp. 160-167 ◽  
Author(s):  
Sheng Xiang Chen ◽  
Jin Long Luo ◽  
Pin Wu Li ◽  
Xun Zhang ◽  
Cheng Wei Ao ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Green Tea ◽  
Pesticide Residues ◽  
Sensory Quality ◽  
Soluble Solids ◽  
Cleaning Process ◽  
Tea Leaves ◽  
Fresh Leaf ◽  
Cleaning Technology

This experiment was conducted to study the new shoot, bud and leaf of Fuding Dabai Tea, which was picked and purchased from Zhongfeng Tea Garden in Ya'an famous mountain area. The sensory quality, contents, pesticide residues and heavy metals of fresh leaves and green tea were studied and compared. The total soluble solids content and turbidity of water samples before and after the cleaning process were determined. The results showed that: (1) the weighted total score of sensory evaluation of finished tea added with fresh leaf cleaning technology was 91.15, which was 2.45 points higher than that of the control (without fresh leaf cleaning), and increased by 2.76%. (2) Fresh leaf cleaning process can significantly reduce the content of tea polyphenols, caffeine and water extract, and the ratio of phenol to ammonia, but has no significant effect on the content of amino acid and soluble sugar. (3) The total soluble solids of Q 2 are 4.3 times as much as Q1, and the turbidity of Q2 is 37.2 times as much as Q1. Cleaning process of fresh leaves can significantly reduce the indexes of agricultural residues and heavy metals. In conclusion, the cleaning process of fresh tea leaves can improve the sensory quality of tea to a certain extent, significantly reduce the content of bitter and astringent substances in tea leaves, effectively clean the surface impurities of fresh tea leaves, reduce pesticide residues and heavy metal content.

scholarly journals A pedestrian detection algorithm for low light and dense crowd Based on improved YOLO algorithm

2022 ◽  
Vol 355 ◽  
pp. 03020
Author(s):  
Yitong Mao
Keyword(s):  
Real Time ◽  
Pedestrian Detection ◽  
Detection Algorithm ◽  
Low Light ◽  
Convolutional Network ◽  
Detection Model ◽  
Aerial View ◽  
Weak Light ◽  
Ap Index ◽  
Dense Crowd

The real-time pedestrian detection algorithm requires the model to be lightweight and robust. At the same time, the pedestrian object detection problem has the characteristics of aerial view Angle shooting, object overlap and weak light, etc. In order to design a more robust real-time detection model in weak light and crowded scene, this paper based on YOLO, raised a more efficient convolutional network. The experimental results show that, compared with YOLOX Network, the improved YOLO Network has a better detection effect in the lack of light scene and dense crowd scene, has a 5.0% advantage over YOLOX-s for pedestrians AP index, and has a 44.2% advantage over YOLOX-s for fps index.

scholarly journals OPTICAL BLUR DISTURBS – THE INFLUENCE OF OPTICAL-BLURRED IMAGES IN PHOTOGRAMMTRY

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 383-388
Author(s):  
T. Sieberth
Keyword(s):  
Target Detection ◽  
Camera Calibration ◽  
Light Field ◽  
Negative Influence ◽  
Motion Blur ◽  
Automatic Target Detection ◽  
Experienced Operator ◽  
Optical Blur ◽  
Blurred Images

Abstract. Photogrammetric processes such as camera calibration, feature and target detection and referencing are assumed to strongly depend on the quality of the images that are provided for the process. Consequently, motion and optically blurred images are usually excluded from photogrammetric processes to supress their negative influence. To evaluate how much optical blur is acceptable and how large the influence of optical blur is on photogrammetric procedures a variety of test environments were established. These were based upon previous motion blur research and included test fields for the analysis of camera calibration. For the evaluation, a DSLR camera as well as Lytro Illum light field camera were used. The results show that optical blur has a negative influence on photogrammetric procedures, mostly automatic target detection. With the intervention of an experienced operator and the use of semi-automatic tools, acceptable results can be established.

scholarly journals A Mathematical Study of Barcelona Metro Network

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 557
Author(s):  
Irene Mariñas-Collado ◽  
Elisa Frutos Bernal ◽  
Maria Teresa Santos Martin ◽  
Angel Martín del Rey ◽  
Roberto Casado Vara ◽  
...  
Keyword(s):  
Clustering Analysis ◽  
Transportation Network ◽  
Point Of View ◽  
Statistical Point ◽  
Transport Services ◽  
Urban Public Transport ◽  
The Common ◽  
Subway Stations ◽  
Metro Network

The knowledge of the topological structure and the automatic fare collection systems in urban public transport produce many data that need to be adequately analyzed, processed and presented. These data provide a powerful tool to improve the quality of transport services and plan ahead. This paper aims at studying, from a mathematical and statistical point of view, the Barcelona metro network; specifically: (1) the structural and robustness characteristics of the transportation network are computed and analyzed considering the complex network analysis; and (2) the common characteristics of the different subway stations of Barcelona, based on the passenger hourly entries, are identified through hierarchical clustering analysis. These results will be of great help in planning and restructuring transport to cope with the new social conditions, after the pandemic.

Die Bonding Issues on Silicon Carbide Diodes

2006 ◽  
Vol 527-529 ◽  
pp. 875-878 ◽  
Author(s):  
Seung Yong Lee ◽  
Jang Sub Lee ◽  
Tae Hong Kim ◽  
Sung Yong Choi ◽  
Hak Jong Kim ◽  
...  
Keyword(s):  
Shear Test ◽  
Vertical Structure ◽  
Optical Microscope ◽  
Device Fabrication ◽  
Cleaning Process ◽  
X Ray ◽  
The Third ◽  
Bottom Side ◽  
Die Bonding

We report on the die bonding processes and how the surface roughness and metallization schemes affect the processes of die bonding in 4H-SiC device fabrication using a soldering test and die shear test (DST) with differently prepared 4H-SiC samples. The first set of samples (FZ#1 and FZ#2) was capped with sequentially evaporated Ti and Au on an annealed Ni layer. The second set of samples (FZ#3 and FZ#4) and the third set of samples (FZ#5 and FZ#6) were prepared by 4μm-thick Au electroplating on an annealed Ni layer and an un-annealed Ni layer, respectively. The quality of the soldering, such as the solder coverage, void, and adhesion, was characterized by optical microscope, X-ray microprobe, and DST. We found that the samples (FZ#4 and FZ#6) deposited by Au electroplating on C-face (bottom-side) 4H-SiC provided a satisfactory result for the tests of solder coverage, void, and DST and also realized the cleaning process prior to the electroplating and soldering was the most crucial in the die packaging processes of vertical structure devices. The void fraction measured by X-ray microprobe for the samples, FZ#4 and FZ#6 was 2.2% (average for 5 samples) and 0.8% (average for 3 samples), respectively.

scholarly journals Pedestrian detection algorithm in traffic scene based on weakly supervised hierarchical deep model

2016 ◽  
Vol 14 (1) ◽  
pp. 172988141769231 ◽  
Author(s):  
Yingfeng Cai ◽  
Youguo He ◽  
Hai Wang ◽  
Xiaoqiang Sun ◽  
Long Chen ◽  
...  
Keyword(s):  
Deep Learning ◽  
Pedestrian Detection ◽  
Recognition Rate ◽  
Detection Algorithm ◽  
Training Methods ◽  
Two Dimensional ◽  
Data Set ◽  
Deep Model ◽  
Unsupervised Training ◽  
Weakly Supervised

The emergence and development of deep learning theory in machine learning field provide new method for visual-based pedestrian recognition technology. To achieve better performance in this application, an improved weakly supervised hierarchical deep learning pedestrian recognition algorithm with two-dimensional deep belief networks is proposed. The improvements are made by taking into consideration the weaknesses of structure and training methods of existing classifiers. First, traditional one-dimensional deep belief network is expanded to two-dimensional that allows image matrix to be loaded directly to preserve more information of a sample space. Then, a determination regularization term with small weight is added to the traditional unsupervised training objective function. By this modification, original unsupervised training is transformed to weakly supervised training. Subsequently, that gives the extracted features discrimination ability. Multiple sets of comparative experiments show that the performance of the proposed algorithm is better than other deep learning algorithms in recognition rate and outperforms most of the existing state-of-the-art methods in non-occlusion pedestrian data set while performs fair in weakly and heavily occlusion data set.

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