Research
Papers with abstracts and visual abstracts. Computer vision, image matching, brain-signal decoding and optimization.
Decoding Visual Information from Neural Signals: Image Reconstruction Based on Joint fMRI and EEG Analysis
A multimodal architecture that jointly processes fMRI and EEG signals to reconstruct visual stimuli, with contrastive alignment to CLIP and a two-stage diffusion generation pipeline.
Evidential Image Matching: Predicting Transformation Sequences to Derive One Image from Another
Plagiarism detection reformulated as predicting the sequence of transformations that derives one image from another, with an encoder–decoder model and the Canonical Jaccard Index.
Pairwise Image Matching for Plagiarism Detection
A siamese network with a weight-shared encoder, symmetric fusion and a similarity head, trained with plagiarism-mimicking augmentations to minimise false positives in pairwise image plagiarism detection.
Enhancing fMRI Data Decoding with Spatiotemporal Characteristics in Limited Dataset
An fMRI decoding methodology for small datasets that combines subject-specific brain activity masks with an encoder based on Riemannian geometry.
Forecasting fMRI Images From Video Sequences: Linear Model Analysis
A method for approximating fMRI readings from the video sequence a person watches, based on a linear model for each voxel and a time-invariant hemodynamic response.
Decentralized Optimization with Coupled Constraints
Lower complexity bounds for decentralized optimization with affine coupled constraints, and the first linearly convergent first-order decentralized algorithm that achieves them.