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Predicting Mood Disorder Symptoms using Interpretable Multimodal Dynamic Atte...
A novel, interpretable multimodal classification method to identify symptoms of mood disorders using audio, video and text collected from a smartphone application. -
Leapfrogging for parallelism in deep neural networks
The dataset used in the paper is a neural network with L layers numbered 1,..., L, in which each of the hidden layers has N neurons. -
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 -
NITI: INTEGER TRAINING
The dataset used in this paper is MNIST, CIFAR10, and ImageNet. -
Batch Inverse-Variance Weighting: Deep Heteroscedastic Regression
Heteroscedastic regression is the task of supervised learning where each label is subject to noise from a different distribution. This noise can be caused by the labelling... -
SolarNet: A Deep Learning Framework to Map Solar Power Plants in China from S...
A deep learning framework to map solar power plants from large-scale satellite imagery data -
Deep Meta Functionals for Shape Representation
A new method for 3D shape reconstruction from a single image, in which a deep neural network directly maps an image to a vector of network weights. -
Parking Analytics Framework using Deep Learning
A dataset for parking analytics using deep learning and image processing. -
Oxford Pets
The dataset used in the paper is a collection of trained networks and their corresponding datasets. -
Continuum Attention for Neural Operators
The dataset is not explicitly described in the paper, but it is mentioned that the authors used it to train and test their neural operator architectures. -
DRiLLS: Deep Reinforcement Learning for Logic Synthesis
Logic synthesis requires extensive tuning of the synthesis optimization flow where the quality of results (QoR) depends on the sequence of optimizations used. The authors... -
Learning Whole Heart Mesh Generation From Patient Images For Computational Si...
A fast and automated deep-learning method to construct simulation-suitable models of the heart from medical images. -
Automatic Detection and Classification of Symbols in Engineering Drawings
A method of finding and classifying various components and objects in a design diagram, drawing, or planning layout is proposed. -
DeepTagRec: A Tag Recommendation Framework
A content-cum-user based deep learning framework for tag recommendation model which takes advantage of the content of the question text and is further enhanced by the rich... -
Face Recognition using Transferred Deep Learning for Feature Extraction
A dataset for face recognition using transferred deep learning for feature extraction -
Deep learning-based dataset for computer-aided detection of medical images
Deep learning-based dataset for computer-aided detection of medical images