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Catalog of Visual-like Morphologies
A catalog of visual-like morphologies in the 5 Candels fields using deep-learning -
SDSS Galaxy Morphology Catalog
A catalog of broad morphology of SDSS galaxies -
Pan-STARRS morphology catalog
A catalog of broad morphology of Pan-STARRS galaxies based on deep learning -
Deep learning-based dataset for computer-aided detection of medical images
Deep learning-based dataset for computer-aided detection of medical images -
FCD dataset for automatic detection of FCD on MRI
Focal cortical dysplasia (FCD) dataset for automatic detection of FCD on magnetic resonance images (MRI) -
Genetic Algorithm based hyper-parameters optimization for transfer Convolutio...
Hyperparameter optimization for transfer Convolutional Neural Networks (CNN) using Genetic Algorithm -
Norm-based Generalization Bounds for Compositionally Sparse Neural Networks
The dataset used in this paper is a multilayered sparse neural network, specifically a convolutional neural network. -
SqueezeJet: High-level Synthesis Accelerator
Deep convolutional neural networks have dominated the pattern recognition scene by providing much more accurate solutions in computer vision problems such as object recognition... -
Convolutional-LSTM for Multi-Image to Single Output Medical Prediction
Medical head CT-scan imaging has been successfully combined with deep learning for medical diagnostics of head diseases and lesions. A custom dataset was used for this study. -
Visual Context-Aware Convolution Filters for Transformation-Invariant Neural ...
The proposed framework generates a unique set of context-dependent filters based on the input image, and combines them with max-pooling to produce transformation-invariant... -
Resource-Frugal Classification and Analysis of Pathology Slides Using Image E...
Pathology slides of lung malignancies are classified using resource-frugal convolution neural networks (CNNs) that may be deployed on mobile devices. -
Deep Epitomic Convolutional Neural Networks
Deep convolutional neural networks have recently proven extremely competitive in challenging image recognition tasks. This paper proposes the epitomic convolution as a new... -
Very Deep Convolutional Networks for Large-Scale Image Recognition
The dataset consists of 60,000 images of objects in 200 categories, with 300 images per category. -
Dataset for Energy-Efficient Deep Neural Networks
The dataset used in this paper is a collection of 25 state-of-the-art deep neural networks (DNNs) with different architectures and sizes. -
Tied Block Convolution: Leaner and Better CNNs with Shared Thinner Filters
Convolution is the main building block of convolutional neural networks (CNN). We observe that an optimized CNN often has highly correlated filters as the number of channels... -
Tensor decomposition to Compress Convolutional Layers in Deep Learning
Feature extraction for tensor data serves as an important step in many tasks such as anomaly detection, process monitoring, image classification, and quality control. -
A Novel Co-design Peta-scale Heterogeneous Cluster for Deep Learning Training
Large scale deep Convolution Neural Networks (CNNs) increasingly demands the computing power. -
Transform Quantization for CNN Compression
The dataset used in this paper is a collection of convolutional neural network (CNN) weights, which are compressed using transform quantization. -
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... -
CNN Models
The dataset used in this paper is a large variety of popular CNN models, such as straight-forward, complicated-connected, and grouped architectures.
