69 citations · 112 across the 5 of their papers we have counts for
5 papers
A request for clarity over the End of Sequence token in the Self-Critical Sequence Training
Jia Cheng Hu, Roberto Cavicchioli, Alessandro Capotondi
The Image Captioning research field is currently compromised by the lack of transparency and awareness over the End-of-Sequence token (<Eos>) in the Self-Critical Sequence Training…
Exploiting Multiple Sequence Lengths in Fast End to End Training for Image Captioning
Jia Cheng Hu, Roberto Cavicchioli, Alessandro Capotondi
We introduce a method called the Expansion mechanism that processes the input unconstrained by the number of elements in the sequence. By doing so, the model can learn more effecti…
Exploring the sequence length bottleneck in the Transformer for Image Captioning
Jia Cheng Hu, Roberto Cavicchioli, Alessandro Capotondi
Most recent state of the art architectures rely on combinations and variations of three approaches: convolutional, recurrent and self-attentive methods. Our work attempts in laying…
A C-DAG task model for scheduling complex real-time tasks on heterogeneous platforms: preemption matters
Houssam-Eddine Zahaf, Nicola Capodieci, Roberto Cavicchioli +2
Recent commercial hardware platforms for embedded real-time systems feature heterogeneous processing units and computing accelerators on the same System-on-Chip. When designing com…
Efficient deconvolution methods for astronomical imaging: algorithms and IDL-GPU codes
M. Prato, R. Cavicchioli, L. Zanni +2
The Richardson-Lucy method is the most popular deconvolution method in astronomy because it preserves the number of counts and the non-negativity of the original object. Regulariza…