33 citations · 51 across the 19 of their papers we have counts for
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cs.CV2024
Biologically-inspired Semi-supervised Semantic Segmentation for Biomedical Imaging
Luca Ciampi, Gabriele Lagani, Giuseppe Amato +1
We propose a novel bio-inspired semi-supervised learning approach for training downsampling-upsampling semantic segmentation architectures. The first stage does not use backpropaga…
cs.CV2024★ 1 cited
Mind the Prompt: A Novel Benchmark for Prompt-based Class-Agnostic Counting
Luca Ciampi, Nicola Messina, Matteo Pierucci +3
Recently, object counting has shifted towards class-agnostic counting (CAC), which counts instances of arbitrary object classes never seen during model training. With advancements…