Tootfinder

smallNet: Implementation of a convolutional layer in tiny FPGAs
Fernanda Zapata Bascu\~n\'an, Alan Ezequiel Fuster
https://arxiv.org/abs/2509.25391 https://

smallNet: Implementation of a convolutional layer in tiny FPGAs
Since current neural network development systems in Xilinx and VLSI require codevelopment with Python libraries, the first stage of a convolutional network has been implemented by developing a convolutional layer entirely in Verilog. This handcoded design, free of IP cores and based on a filter polynomial like structure, enables straightforward deployment not only on low cost FPGAs but also on SoMs, SoCs, and ASICs. We analyze the limitations of numerical representations and compare our impleme…

Spectral Prefiltering of Neural Fields
Mustafa B. Yaldiz, Ishit Mehta, Nithin Raghavan, Andreas Meuleman, Tzu-Mao Li, Ravi Ramamoorthi
https://arxiv.org/abs/2510.08394 https://

Spectral Prefiltering of Neural Fields
Neural fields excel at representing continuous visual signals but typically operate at a single, fixed resolution. We present a simple yet powerful method to optimize neural fields that can be prefiltered in a single forward pass. Key innovations and features include: (1) We perform convolutional filtering in the input domain by analytically scaling Fourier feature embeddings with the filter's frequency response. (2) This closed-form modulation generalizes beyond Gaussian filtering and supports…