Abstract: Multimodal medical image fusion (MMIF) extracts the most meaningful information from multiple source images, enabling a more comprehensive and accurate diagnosis. Achieving high-quality ...

A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving generative AI models. The method reinterpreted Schrödinger bridge models as ...

The encoder employs a DenseNet-B (bottleneck) architecture with three dense blocks separated by transition layers. Each bottleneck layer consists of a 1x1 convolution (expanding to 4x growth rate) ...

Abstract: We propose an end-to-end deep neural encoder-decoder model to encode and decode brain activity in response to naturalistic stimuli using functional magnetic resonance imaging (fMRI) data.

Research conducted 2026-03-11 covering sherpa-onnx (k2-fsa/csukuangfj), onnx-asr (istupakov), HuggingFace Optimum, and the ONNX spec for external data. All tensors can be consolidated into a single ...