4 papers
No One-Size-Fits-All Neurons: Task-based Neurons for Artificial Neural Networks
Feng-Lei Fan, Meng Wang, Hang-Cheng Dong +2
In the past decade, many successful networks are on novel architectures, which almost exclusively use the same type of neurons. Recently, more and more deep learning studies have b…
On Expressivity of Height in Neural Networks
Feng-Lei Fan, Ze-Yu Li, Huan Xiong +1
In this work, beyond width and depth, we augment a neural network with a new dimension called height by intra-linking neurons in the same layer to create an intra-layer hierarchy,…
Retinal Vessel Segmentation via Neuron Programming
Tingting Wu, Ruyi Min, Peixuan Song +3
The accurate segmentation of retinal blood vessels plays a crucial role in the early diagnosis and treatment of various ophthalmic diseases. Designing a network model for this task…
Don't Fear Peculiar Activation Functions: EUAF and Beyond
Qianchao Wang, Shijun Zhang, Dong Zeng +4
In this paper, we propose a new super-expressive activation function called the Parametric Elementary Universal Activation Function (PEUAF). We demonstrate the effectiveness of PEU…