Orlando Moreira — accepted AI-conference papers

2025

MEET: Towards Memory-Efficient Temporal Sparse Deep Neural Networks

Zeqi Zhu, Ibrahim Batuhan Akkaya, Luc Waeijen, Egor Bondarev, Arash Pourtaherian, Orlando Moreira

CVPR 2025poster

Deep Neural Networks (DNNs) are accurate but compute-intensive, leading to substantial energy consumption during inference. Exploiting temporal redundancy through \Delta-\Sigma convolution in video processing has proven to greatly enhance computation efficiency. However, temporal \Delta-\Sigma DNNs…

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2024

ELSE: Efficient Deep Neural Network Inference through Line-based Sparsity Exploration

Zeqi Zhu*, Alberto Garcia-Ortiz, Luc Waeijen, Egor Bondarev, Arash Pourtaherian, Orlando Moreira

ECCV 2024poster

"Brain-inspired computer architecture facilitates low-power, low-latency deep neural network inference for embedded AI applications. The hardware performance crucially hinges on the quantity of non-zero activations (i.e., events) during inference. Thus, we propose a novel event suppression method, d…

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