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FSCNN: A Fast Sparse Convolution Neural Network Inference System
Convolutional Neural Network (CNN) has demonstrated its success in plentiful computer vision application, but typically accompanies high computation cost and numerous redundant... -
Semi-Self-Supervised Domain Adaptation
A semi-self-supervised domain adaptation technique based on deep convolutional neural networks with a probabilistic diffusion process, requiring minimal manual data annotation. -
Transformer-Based Attention Networks for Continuous Pixel-Wise Prediction
The proposed TransDepth framework for pixel-wise prediction problems involving continuous labels. -
Radiopaedia COVID-19 Lung Infections in Chest CT volumes
The dataset used in this work consists of 9 axial volumes from Radiopaedia consisting of both positive and negative COVID indications. -
Jun et al. COVID-19 Lung Infections in Chest CT volumes
The dataset used in this work consists of 20 volumes from Jun et al. consisting of infections labelled by two radiologists and verified by another experienced radiologist. -
COVID-19 Lung Infections in Chest CT volumes
The dataset used in this work consists of 29 CT volumes from two different sources of lung infection data, resulting from COVID-19. -
Deep Learning Framework for Spatiotemporal Ultrasound Localization Microscopy
Ultrasound Localization Microscopy can resolve the microvascular bed down to a few micrometers. To achieve such performance microbubble contrast agents must perfuse the entire... -
NeuroCLIP: Neuromorphic Data Understanding by CLIP and SNN
Neuromorphic data understanding by CLIP and SNN -
Automatic Conditional Generation of Personalized Social Media Short Texts
A conditional language generation model with Big Five Personality (BFP) feature vectors as input context, which writes human-like short texts. -
Training a U-Net based on a random mode-coupling matrix to recover acoustic i...
A U-Net is trained to recover acoustic interference striations (AISs) from distorted ones. A random mode-coupling matrix model is introduced to generate a large number of... -
Quantitative Analysis of Abnormalities in Gynecologic Cytopathology
Quantitative analysis of abnormalities in gynecologic cytopathology with deep learning -
ExplainFix: Explainable Spatially Fixed Deep Networks
ExplainFix adopts two design principles: the “fixed filters” principle that all spatial filter weights of convolutional neural networks can be fixed at initialization and never... -
Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit...
The proposed rectified binary convolutional networks (RBCNs) are used to improve the performance of 1-bit DCNNs for mobile and AI chips based applications. -
TORCHSPARSE: EFFICIENT POINT CLOUD INFERENCE ENGINE
Deep learning on point clouds has received increased attention thanks to its wide applications in AR/VR and autonomous driving. -
New Normal: Cooperative Paradigm for Covid-19
The proposed scheme uses IoT based health monitoring and CNN based object detection methods to detect social distancing violations and track exposed or infected people. -
WCE curated colon disease dataset for deep learning
WCE curated colon disease dataset for deep learning -
LSUN: Construction of a large-scale image dataset using deep learning with hu...
LSUN Church dataset is a large-scale image dataset containing 30,000 images of churches. -
Deep unsupervised learning using nonequilibrium thermodynamics
Deep unsupervised learning using nonequilibrium thermodynamics -
Deep learning for decoding of linear codes-a syndrome-based approach
Deep learning for decoding of linear codes - a syndrome-based approach -
Error Correction Code Transformer
Error correction code transformer for decoding linear codes
