Kediska Ogaanshaha Shayga Erayada Furan

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Waa maxay awoodda qeexidda ereyada-furan ogaanshaha shayga?
   • Ogaanshaha kaliya qaybaha lagu arkay sanduuqyada inta lagu jiro tababarka
   • U ordaya si ka dhakhso badan dhammaan qalabka kale ee wax baadha
   • Ogaanshaha walxaha lagu sifeeyay qoraal aan sabab lahayn, oo ay ku jiraan qaybaha aan la arki karin
   • Ku shaqaynta kaliya sawirada cawl
2. In a common embedding-based open-vocabulary detector, how are candidate regions matched to user-supplied labels?
   • By using only the region's average brightness
   • By comparing visual-region features with text embeddings in a compatible representation space
   • By choosing labels alphabetically without visual features
   • By restricting every model to the original COCO class list
3. Ilaha tababarka ka hor inta badan awood u siinaya in la ogaado ereyada furan?
   • Lammaanaha qoraalka-muuqaalka-weyn ee loo isticmaalo in lagu barto meel bannaan oo luqad-aragti ah
   • Qayb yar oo sanduuqyo ah oo si fiican u calaamadsan
   • Duubabka maqalka ah
   • Qalabka xogta nambarka gacanta lagu qoray
4. What replaces fixed per-class classifier weights in a common embedding-based open-vocabulary design?
   • The camera's physical image sensor
   • The bounding-box coordinate system
   • All visual features with random file identifiers
   • Representations of the supplied text labels used for similarity-based classification
5. Midkee ka mid ah kuwan tusaalaha ereyada furan ama qaabka ogaanshaha?
   • ResNet-50 oo keliya
   • Dejinta DINO
   • K- cad oo macnaheedu yahay qoraal kooxeed
   • Macro xaashida
6. What does an open-vocabulary detector's ability to use a new text category imply?
   • It guarantees accurate detection of every nameable object
   • The category must have been absent from every pretraining image and caption
   • It can attempt localization through learned vision-language associations, with accuracy requiring evaluation
   • It needs no visual features or bounding-box output
7. What output distinguishes text-conditioned object detection from simply saying that an image contains a named category?
   • Only a whole-image tag with no object location
   • Only the text prompt's word count
   • Only the image's dimensions and filename
   • Locations such as bounding boxes for the matching objects
8. Before using open-vocabulary predictions to auto-label a new domain, what should a dataset team check?
   • The boxes and labels under representative prompts, thresholds, and domain conditions
   • Assume text-conditioned predictions are automatically ground truth
   • Verify only that the label strings contain no spelling errors
   • Discard all visual inspection because image-text pretraining guarantees accuracy