GA-Based Optimization of SURF Algorithm and Realization Based on Vivado-HLS

Özdemir, Hüseyin; Sever, Refik; Polat, Övünç

doi:10.18280/ts.360501

Cited by 9 publications

(6 citation statements)

References 12 publications

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“…Hao et al [18] proposed a departure-arrival model of intersections with cooperative control, solved it with genetic algorithm (GA), and thus realized the cooperative control of phase difference on urban trunk roads. With the aid of the GA, Nguyen et al optimized the rules of the fuzzy controller of traffic signals at intersections, and achieved the optimal signal timing [19], [20].…”

Section: Literature Reviewmentioning

confidence: 99%

Intersection Traffic Control Based on Multi-Objective Optimization

Mou

2020

IEEE Access

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Currently, most traffic control methods at intersections rely on the control of signal lights. However, most signal lights operate in the traditional fixed timing mode, which cannot adjust the timing based on the time-varying traffic flow. To solve the problem, this paper constructs a signal timing control model to optimize road capacity, delay time and the number of stops at the intersections, under the following constraints: cycle time, effective green light time and the maximum number of vehicles in each direction of intersection. To solve the model, the standard dragonfly algorithm (DA) was improved by a hybrid mutation operator, which ensures the diversity of solution set. The proposed model and algorithm were compared with the Webster model through simulations in an actual scene and on a virtual platform. The comparison fully proves the advantages of our model and algorithm.

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Section: Literature Reviewmentioning

confidence: 99%

Intersection Traffic Control Based on Multi-Objective Optimization

Mou

2020

IEEE Access

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“…For the three ways of face recognition, different descriptors and classifiers are used in order to validate our approach. For feature extraction, we utilize two different features: (1) hand-crafted features by exploiting the most used and efficient descriptors, which are the SURF Özdemir et al [27] and the HOG [28], and (2) learned features extracted from the final layers of the pre-trained Inception-v3 architecture model [29]. As regards classification, our suggested method is evaluated by using the k Nearest Neighbors (k-NN) Cunningham and Delany [30] combined with the K Dimensional Tree (KD-Tree) [31] and Support Vector Machine (SVM) [32] classifiers as classical methods and the pre-trained Inception-v3 model as a deep learning method.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study Based on De-Occlusion and Reconstruction of Face Images in Degraded Conditions

Ouannes¹,

Khalifa²,

Amara³

2021

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In the recent years, the face recognition task has attracted the attention of researchers due to its efficiency in several domains such as surveillance and access control. Unfortunately, there are multiple challenges that decrease the performance of face recognition. Partial occlusion is the most challenging one since it often causes a great lack of information. The main purpose of this paper is to prove that facial reconstruction improves the results of facial recognition compared to de-occlusion and full-face recognition in the presence of occlusion. Our objective is to achieve occluded-face recognition, de-occluded-face recognition, and reconstructed-face recognition. Regarding face reconstruction, we introduce two different methods based on Laplacian pyramid blending and CycleGANs. In order to validate our work, we perform two different feature extraction techniques: hand-crafted features and learned features exploiting the final layers of a pre-trained deep architecture model. The experimental results on the EURECOM Kinect Face Dataset (EKFD) and the IST-EURECOM Light Field Face Database (IST-EURECOM LFFD) show that the proposed face reconstruction approach, compared with the face de-occlusion and occluded-face recognition ones, clearly improves the face recognition task. Our method boosts the classification performance in comparison with the state-of-the-art methods, achieving 94.66% on EKFD and 72.35% on IST-EURECOM LFFD.

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“…e dispatching of common rail dual AGVs is a typical TRSP in factories to quickly dispatch materials between tanks or automatically schedule express delivery in warehouses. Traditionally, this novel and specific problem is solved by simple heuristic algorithms, such as genetic algorithms (GA) and [7][8][9][10] particle swarm optimization (PSO) [11][12][13]. Due to the sheer scale of the problem, it is difficult for these algorithms to converge to the global optimal solution.…”

Section: Introductionmentioning

confidence: 99%

A Novel Scheduling Algorithm for Common Rail Dual Automatic Guided Vehicles Particle Filtering Algorithm for Industrial Process Control

Gao

Lou

Lü

2021

Mathematical Problems in Engineering

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This paper explores deep into the collaborative scheduling of common rail dual automatic guided vehicles (AGVs). Firstly, a dual AGV scheduling model was constructed to minimize the overall time of material distribution. Then, a novel scheduling algorithm was developed to dynamically plan the orders based on time windows. To effectively minimize the distribution time, heuristic algorithms were adopted to initialize the distribution order of materials. On this basis, the collaboration between the two AGVs was innovatively designed based on dynamic planning and time windows, making up for the defects of traditional methods in AGV cooperation. This greatly shortens the running time of the entire system in material distribution. The computing results fully demonstrate the efficiency and rationality of our algorithm. Finally, our algorithm was proved to be superior to the benchmark method through experiments on actual industrial instances.

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GA-Based Optimization of SURF Algorithm and Realization Based on Vivado-HLS

Cited by 9 publications

References 12 publications

Intersection Traffic Control Based on Multi-Objective Optimization

Intersection Traffic Control Based on Multi-Objective Optimization

Comparative Study Based on De-Occlusion and Reconstruction of Face Images in Degraded Conditions

A Novel Scheduling Algorithm for Common Rail Dual Automatic Guided Vehicles Particle Filtering Algorithm for Industrial Process Control

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