Nextdet: efficient sparse-to-dense object detection with attentive feature aggregation

HIGHLIGHTS

• who: Priyank Kalgaonkar and Mohamed El-Sharkawy from the Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology Indianapolis have published the paper: NextDet: Efficient Sparse-to-Dense Object Detection with Attentive Feature Aggregation, in the Journal: Future Internet 2022, 355 of /2022/
• what: The scope of the work presented within this paper proposes a modern network called NextDet efficiently detect objects of multiple classes which utilizes CondenseNeXt an award-winning lightweight image classification convolutional neural network algorithm with reduced number of FLOPs and parameters as the backbone efficiently extract and aggregate . . .
  

   

  

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