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+imagery+poses+a+significant+challenge%252C+despite+its+critical+role+in+enabling+precise+analysis+and+informed+decision-making+across+various+sectors.+This+scarcity+is+primarily+due+to+atmospheric+conditions%252C+seasonal+variations%252C+and+limited+geographical+coverage%252C+which+complicates+the+application+of+Artificial+Intelligence+(AI)+in+EO.+Data+augmentation%252C+a+widely+used+technique+in+AI+that+involves+generating+additional+data+mainly+through+parameterized+image+transformations%252C+has+been+employed+to+increase+the+volume+and+diversity+of+data.+However%252C+this+method+often+falls+short+in+generating+sufficient+diversity+across+key+semantic+axes%252C+adversely+affecting+the+accuracy+of+EO+applications.+To+address+this+issue%252C+we+propose+a+novel+four-stage+approach+aimed+at+improving+the+diversity+of+augmented+data+by+integrating+diffusion+models.+Our+approach+employs+meta-prompts+for+instruction+generation%252C+harnesses+general-purpose+vision-language+models+for+generating+rich+captions%252C+fine-tunes+an+Earth+Observation+diffusion+model%252C+and+iteratively+augments+data.+We+conducted+extensive+experiments+using+four+different+data+augmentation+techniques%252C+and+our+approach+consistently+demonstrated+improvements%252C+outperforming+the+established+augmentation+methods%252C+revealing+its+effectiveness+in+generating+semantically+rich+and+diverse+EO+images.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.8329993f1e9246fed35d4d575762efbf%3frik%3dT0juWMN519rgMQ%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Diffusion+Models+for+Data+Augmentation&FORM=IRPRST&ck=40FEF472120ABE846E7773C924D4CF18&selectedIndex=8&itb=0)
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