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2. Vacant and occupied parking slots have been successfully classified
   by the trained deep classifier in both examples and are marked with inexperienced and purple BBs, respectively.
   Once the parking slots positions are decided in the input image, each detected parking slot is categorized as occupied or vacant utilizing a
   specifically educated ResNet34 deep classifier.
   Trained classifier achieves excessive accuracy in parking slot occupancy classification. The shortage
   of parking space is very pronounced in crowded urban areas the
   place the available parking area is in high demand all through
   the entire day. Furthermore, KNN filtering reveals a excessive performance
   improvement in FBMS with multiple target objects, demonstrating that by sampling options, it may
   possibly successfully extract generalized options for multi-objects by slot attention. Random:
   The active learning method with random sampling
   strategy. However, our methodology has a number of vital differences:
   1) we introduce a novel structure for bidirectional joint a
   number of intent detection and slot filling;
   2) we make use of supervised contrastive studying and
   self-distillation to prepare the proposed joint mannequin effectively.

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