The workflow of EGA-BPNN. by Xiying Wang (4859998)

“…To address these problems, a genetic algorithm (GA) is adopted for optimizing the BPNN, and the EGA-BPNN model is used to predict irrigation flow in agricultural fields. …”

S1 Data - by Xiying Wang (4859998)

“…To address these problems, a genetic algorithm (GA) is adopted for optimizing the BPNN, and the EGA-BPNN model is used to predict irrigation flow in agricultural fields. …”

Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf by Muhammad Awais (263096)

Fusion effectiveness of 6 groups of images. by Yandong Liu (11893664)

“…Finally, in the context of a complex fusion process, the multi-agent fusion model performs the fusion task through the collaborative interaction of multiple fusion agents. …”

Overall flowchart of Multi-agent fusion model. by Yandong Liu (11893664)

“…Finally, in the context of a complex fusion process, the multi-agent fusion model performs the fusion task through the collaborative interaction of multiple fusion agents. …”

Fusion performance of 3 groups fusion structures. by Yandong Liu (11893664)

“…Finally, in the context of a complex fusion process, the multi-agent fusion model performs the fusion task through the collaborative interaction of multiple fusion agents. …”

Fusion rule set. by Yandong Liu (11893664)

“…Finally, in the context of a complex fusion process, the multi-agent fusion model performs the fusion task through the collaborative interaction of multiple fusion agents. …”

Comparison with existing SOTA techniques. by Yasir Khan Jadoon (21433231)

“…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …”

Proposed inverted residual parallel block. by Yasir Khan Jadoon (21433231)

“…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …”

Inverted residual bottleneck block. by Yasir Khan Jadoon (21433231)

“…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …”

Proposed architecture testing phase. by Yasir Khan Jadoon (21433231)

“…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …”

Sample classes from the HMDB51 dataset. by Yasir Khan Jadoon (21433231)

“…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …”

Sample classes from UCF101 dataset [40]. by Yasir Khan Jadoon (21433231)

“…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …”

Self-attention module for the features learning. by Yasir Khan Jadoon (21433231)

“…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …”

Residual behavior. by Yasir Khan Jadoon (21433231)

“…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …”

Dongfanghong tractor. by Ningjie Chang (21402721)

“…<div><p>The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance method for mountain tractors based on semantic neural network and laser SLAM was studied. …”

Experimental equipment parameters. by Ningjie Chang (21402721)

“…<div><p>The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance method for mountain tractors based on semantic neural network and laser SLAM was studied. …”

Coordinate Conversion Process. by Ningjie Chang (21402721)

“…<div><p>The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance method for mountain tractors based on semantic neural network and laser SLAM was studied. …”

Data for parameters. by Ningjie Chang (21402721)

“…<div><p>The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance method for mountain tractors based on semantic neural network and laser SLAM was studied. …”

Semantic Label Addition Process. by Ningjie Chang (21402721)

“…<div><p>The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance method for mountain tractors based on semantic neural network and laser SLAM was studied. …”