3 papers
cs.CV2025
COLORA: Efficient Fine-Tuning for Convolutional Models with a Study Case on Optical Coherence Tomography Image Classification
Mariano Rivera, Angello Hoyos
We introduce CoLoRA (Convolutional Low-Rank Adaptation), a parameter-efficient fine-tuning method for convolutional neural networks (CNNs). CoLoRA extends LoRA to convolutional lay…
cs.CV2023
Attentive VQ-VAE
Angello Hoyos, Mariano Rivera
We present a novel approach to enhance the capabilities of VQ-VAE models through the integration of a Residual Encoder and a Residual Pixel Attention layer, named Attentive Residua…
cs.CV2023
Hadamard Layer to Improve Semantic Segmentation
Angello Hoyos, Mariano Rivera
The Hadamard Layer, a simple and computationally efficient way to improve results in semantic segmentation tasks, is presented. This layer has no free parameters that require to be…