CBR test results. by Shoujie Wang (18326754)

“…The results show that the UCS and CBR values enhanced significantly with the increase in curing time. However, the moisture content and pH of the stabilized soil exhibited a decreasing trend. …”

Change in moisture content of stabilized soil. by Shoujie Wang (18326754)

“…The results show that the UCS and CBR values enhanced significantly with the increase in curing time. However, the moisture content and pH of the stabilized soil exhibited a decreasing trend. …”

Relationship between UCS and curing time. by Shoujie Wang (18326754)

“…The results show that the UCS and CBR values enhanced significantly with the increase in curing time. However, the moisture content and pH of the stabilized soil exhibited a decreasing trend. …”

Strength characteristic curve of stabilized soil. by Shoujie Wang (18326754)

“…The results show that the UCS and CBR values enhanced significantly with the increase in curing time. However, the moisture content and pH of the stabilized soil exhibited a decreasing trend. …”

Change in pH value of stabilized soil. by Shoujie Wang (18326754)

“…The results show that the UCS and CBR values enhanced significantly with the increase in curing time. However, the moisture content and pH of the stabilized soil exhibited a decreasing trend. …”

CBR test results at different curing time. by Shoujie Wang (18326754)

“…The results show that the UCS and CBR values enhanced significantly with the increase in curing time. However, the moisture content and pH of the stabilized soil exhibited a decreasing trend. …”

Distribution of Pre-existing Medical Conditions. by Sepideh Hejazi (16227860)

“…</p><p>Results</p><p>Initial clinical presentations differed significantly, eneralized Estimating Equations (GEE) analysis, adjusted for comorbidities, revealed COVID-19 history was associated with increased platelet counts <i>(P</i> = 0.0311) and decreased facial swelling <i>(P</i> = 0.049) and fever symptom reporting <i>(P</i> < 0.001). …”

Melt Memory Effect on Biaxially Oriented Random Copolyamides: Direct Evidence for Stretch-Induced Crystal Retention above the Equilibrium Melting Point by Yunqi Xu (349428)

Subjects:

Accuracy test results. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Experiment environment and parameter. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Test results for NME and FR. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

DARTS algorithm process. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Comparison result of memory usage. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

LKA model structure. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Test results on different datasets. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Comparison result of memory usage. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Residual configuration. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Test results for P, R, F1, and OA. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Schematic diagram of DARTS-VAN model structure. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

DARTS-VAN model unit search process. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”