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| Row |
Code |
Title |
Year |
Code |
Field |
XML |
View |
| 7301 |
6497 |
Spatial zoning of the quality of life in urban neighborhoods using fuzzy model (study area: Districts no 5 and 6 of Mashhad, Iran) |
0 |
khu-cv-ths-172-45944 |
|
|
17 Time(s) |
| 7302 |
6495 |
A comparative study on statistical and artificial intelligence approaches for potential of landslide zonation , a case study for Tehran province. |
0 |
khu-cv-ths-172-45540 |
|
|
16 Time(s) |
| 7303 |
6550 |
Optimization of Water Distribution Network using Fast Messy Genetic Algorithm (FMGA) (CaseStudy : Water Distribution Network of District 2 of Qazvin) |
0 |
khu-cv-ths-172-78901 |
|
|
20 Time(s) |
| 7304 |
6537 |
Vehicle detection in high resolution satellite images using convolutional neural network |
0 |
khu-cv-ths-172-76781 |
|
|
19 Time(s) |
| 7305 |
6548 |
Detecting military targets and objects (tank)in the images of reconnaissance drones using artificial intelligence deep learning algorithms (YOLOV8) |
0 |
khu-cv-ths-172-78797 |
|
|
19 Time(s) |
| 7306 |
6547 |
Spatial-temporal modeling of local dispersion of carbon monoxide pollutant caused by traffic using particle motion simulation methods (case study: Tehran) |
0 |
khu-cv-ths-172-78796 |
|
|
18 Time(s) |
| 7307 |
6545 |
Optimization of Water Distribution Network using Fast Messy Genetic Algorithm (FMGA) (CaseStudy : Water Distribution Network of District 2 of Qazvin, Iran) |
0 |
khu-cv-ths-172-78794 |
|
|
21 Time(s) |
| 7308 |
6543 |
Detecting military targets and objects in the images of reconnaissance drones using artificial intelligence deep learning algorithms (YOLOV8) |
0 |
khu-cv-ths-172-78211 |
|
|
18 Time(s) |
| 7309 |
6541 |
Spatio-Temporal Analysis of Accident Using Clustering Algorithms |
0 |
khu-cv-ths-181-77850 |
|
|
21 Time(s) |
| 7310 |
6539 |
Derivation of Tasseled Cap Transformation Coefficients for Sentinel-2 data by using Principal component based Procrustes method with Landsat-8 OLI data coefficients |
0 |
khu-cv-ths-172-76986 |
|
|
18 Time(s) |
| 7311 |
6535 |
Spatial and Topologic Modeling of Road Bridges Data based on CityGML |
0 |
khu-cv-ths-172-76001 |
|
|
21 Time(s) |
| 7312 |
6532 |
Accuracy assessment of burned area mapping using spectral indexes |
0 |
khu-cv-ths-172-74337 |
|
|
20 Time(s) |
| 7313 |
6530 |
Utilization of artificial intelligence methods and indicators such as aerial and satellite image texture in preparing agricultural cadaster and comparing the accuracy of maps |
0 |
khu-cv-ths-172-72105 |
|
|
19 Time(s) |
| 7314 |
6528 |
Evaluation of capsule networks in vehicle detetction |
0 |
khu-cv-ths-172-69695 |
|
|
20 Time(s) |
| 7315 |
6526 |
Flood dis charge forcast using artificial intelligence (lstm).(in the study area of keshkan River In lorestan provinc) |
0 |
khu-cv-ths-172-69373 |
|
|
16 Time(s) |
| 7316 |
6524 |
3D object detection of building shapes from lidar data using mask R- CNN model |
0 |
khu-cv-ths-172-69049 |
|
|
35 Time(s) |
| 7317 |
6716 |
-methoxybenzaldehyde [5-2,2-dimethyl1-4,6-dioxan-5-yildene) -4,5-dihydro-1,3,4-thiadiazol-2-ylhydrazine] |
0 |
khu-cv-ths-162-18538 |
|
|
20 Time(s) |
| 7318 |
6714 |
(E)-5(-4-(dimethylamino)benzylidene)hydrazine)-2,3-dihydro-1,3,4-thiadiazol-2-yl)-2,2dimenthyl1-1,3 dioxane-4,6-dione) |
0 |
khu-cv-ths-162-18536 |
|
|
13 Time(s) |
| 7319 |
6613 |
1(Amino-Phenyl)-naphthelen 2-el |
0 |
khu-cv-ths-140-18062 |
|
|
27 Time(s) |
| 7320 |
6627 |
(ROS) |
0 |
khu-cv-ths-151-18188 |
|
|
11 Time(s) |
| 7321 |
6631 |
Co (II) |
0 |
khu-cv-ths-151-18194 |
|
|
13 Time(s) |
| 7322 |
6670 |
ICPOES |
0 |
khu-cv-ths-160-18478 |
|
|
12 Time(s) |
| 7323 |
6666 |
(II) |
0 |
khu-cv-ths-160-18462 |
|
|
15 Time(s) |
| 7324 |
6661 |
Organic geochmistry and oil-source rock correlation of the Sarvak reservior in one of the oilfields from southwest of Iran |
0 |
khu-cv-ths-159-18455 |
|
|
13 Time(s) |
| 7325 |
6647 |
1,3,4-(6H) |
0 |
khu-cv-ths-159-18438 |
|
|
25 Time(s) |
|
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