Search Results for author:
Found 7 papers, 2 papers with code
Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket
To the best of our knowledge, this is the first time that the SNN achieves 80+% accuracy on ImageNet.
Neural Network-Based Histologic Remission Prediction In Ulcerative Colitis
A total of 5105 images of 154 intestinal segments from 87 patients undergoing EC treatment at a center in China between March 2022 and March 2023 are scored according to the Geboes score.
Automotive Object Detection via Learning Sparse Events by Spiking Neurons
Traditional object detection techniques that utilize Artificial Neural Networks (ANNs) face challenges due to the sparse and asynchronous nature of the events these sensors capture.
Auto-Spikformer: Spikformer Architecture Search
The integration of self-attention mechanisms into Spiking Neural Networks (SNNs) has garnered considerable interest in the realm of advanced deep learning, primarily due to their biological properties.
Accurate and Efficient Event-based Semantic Segmentation Using Adaptive Spiking Encoder-Decoder Network
Leveraging the low-power, event-driven computation and the inherent temporal dynamics, spiking neural networks (SNNs) are potentially ideal solutions for processing dynamic and asynchronous signals from event-based sensors.
Discrete Time Convolution for Fast Event-Based Stereo
Inspired by continuous dynamics of biological neuron models, we propose a novel encoding method for sparse events - continuous time convolution (CTC) - which learns to model the spatial feature of the data with intrinsic dynamics.
Deep Learning-based Biological Anatomical Landmark Detection in Colonoscopy Videos
Second, a ResNet-101 based network is used to detect three biological anatomical landmarks separately to obtain the intermediate detection results.
