Spectral Mixer
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Related Articles from SNS
Hyperspectral Image Classification using Spectral-Spatial Mixer Network
arXiv:2511.15692v2 Announce Type: replace Abstract: This paper introduces SS-MixNet, a lightweight and effective deep learning model for hyperspectral image (HSI) classification. The architecture integrates 3D convolutional layers for local spectral-spatial feature extraction with two parallel MLP-style mixer blocks that capture long-range dependencies in spectral and spatial dimensions. A depthwise convolution-based attention mechanism is employed to enhance discriminative capability with...
{\lambda}Split: Self-Supervised Content-Aware Spectral Unmixing for Fluorescence Microscopy
arXiv:2603.23647v2 Announce Type: replace Abstract: In fluorescence microscopy, spectral unmixing aims to recover individual fluorophore concentrations from spectral images that capture mixed fluorophore emissions. Since classical methods operate pixel-wise and rely on least-squares fitting, their performance degrades with increasingly overlapping emission spectra and higher levels of noise, suggesting that a data-driven approach that can learn and utilize a structural prior might lead to...
Brume is a 24-voice multi-timbral desktop synth for the CM5
FM Six operators across twelve algorithm topologies, per-op ratio and level, global feedback, a per-voice FM-index envelope, and a voice-tail state-variable filter with its own envelope — DX-style FM with subtractive shaping on the way out. A desktop multi-timbral music machine with four synthesis engines, a 10″ touch surface, and one cable to your DAW. Brume runs four synthesis engines with a shared voice tail (state-variable filter, amp envelope, modulation router), so patches stay...