80 citations · 80 across the 3 of their papers we have counts for
4 papers
JEPAhead: From Inpainting to Causal Forecasting for Urban Driving
Daniel G. P. Petrini, Davi Pincinato, Fabio Grassiotto +4
We fine-tune a pre-trained V-JEPA1 predictor from bidirectional latent inpainting to action-free causal forecasting while keeping the encoder frozen. Using contiguous past observat…
HW/SW Co-design of a PCM/PWM converter: a System Level Approach based in the SpecC Methodology
Daniel G. P. Petrini, Braz Izaias da Silva Junior
We present a case study applying the SpecC methodology within a system-level hardware/software co-design flow to a PCM-to-PWM converter, the core of a Class-D audio amplifier. The…
Optimizing Breast Cancer Detection in Mammograms: A Comprehensive Study of Transfer Learning, Resolution Reduction, and Multi-View Classification
Daniel G. P. Petrini, Hae Yong Kim
Mammography, an X-ray-based imaging technique, remains central to the early detection of breast cancer. Recent advances in artificial intelligence have enabled increasingly sophist…
Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained EfficientNet-Based Convolutional Network
Daniel G. P. Petrini, Carlos Shimizu, Rosimeire A. Roela +3
Some recent studies have described deep convolutional neural networks to diagnose breast cancer in mammograms with similar or even superior performance to that of human experts. On…