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Spectrum Sensing and Signal Identification with Deep Learning based on Spectra...
A dataset for spectrum sensing and signal identification using deep learning based on spectral correlation function -
A Ray-tracing and Deep Learning Fusion Super-resolution Modeling Method for W...
A dataset for wireless mobile channel modeling, including ray tracing and deep learning fusion super-resolution modeling method for cluster characteristics prediction. -
Feed-Forward Neural Networks on CIFAR-10
Feed-Forward Neural Networks on CIFAR-10 -
AIFNet: Automatic Vascular Function Estimation for Perfusion Analysis Using D...
Perfusion imaging is crucial in acute ischemic stroke for quantifying the salvageable penumbra and irreversibly damaged core lesions. -
deepBF: Malicious URL detection using Self-adjusted Bloom Filter and Evolutio...
Malicious URL detection is an emerging research area due to continuous modernization of various systems, for instance, Edge Computing. In this article, we present a novel... -
Trajectory Estimation Dataset
A dataset of radio measurements in an outdoor setting, used to evaluate the performance of different deep learning architectures for trajectory estimation. -
Authentication of Copy Detection Patterns under Machine Learning Attacks: A S...
Copy detection patterns (CDP) are an attractive technology that allows manufacturers to defend their products against counterfeiting. The main assumption behind the protection... -
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Le...
The dataset used in the paper is a collection of expert demonstrations for various tasks, including robotic manipulation, maze navigation, and Atari games. -
Diagnosing Bottlenecks in Deep Q-Learning Algorithms
The dataset used in the paper is a collection of expert demonstrations for various tasks, including robotic manipulation, maze navigation, and Atari games. -
TREC Deep Learning 2021 Collection
The TREC Deep Learning 2021 collection is a test collection for information retrieval evaluation, adopting a shallow pooling approach. -
NN-EMD: Efficiently Training Neural Networks using Encrypted Multi-sourced Da...
Training complex neural network models using third-party cloud-based infrastructure among multiple data sources is a promising approach among existing machine learning... -
Speech Intelligibility Prediction with DNN-based Performance Measures
The dataset used for speech intelligibility prediction with DNN-based performance measures -
Benchmarking Robustness of Deep Learning Classifiers Using Two-Factor Perturb...
Benchmarking robustness of deep learning classifiers using two-factor perturbation -
Network Transplanting
The dataset used in the paper for network transplanting. -
Coin.AI: A Proof-of-Useful-Work Scheme for Blockchain-Based Distributed Deep ...
The dataset used in this paper is a collection of deep learning models, where each model is trained on a specific problem and evaluated on a validation set. -
Moons, Circles, Spirals, Single Blobs, and Double Blobs
The dataset used in the paper is a 2D dataset with 5 types: Moons, Circles, Spirals, Single Blobs, and Double Blobs. -
Explainable Deep Clustering for Monaural Speech Separation
The proposed X-DC model uses a dataset of mixed speech signals of two, four, or eight speakers. -
Neural Network Training on In-memory-computing Hardware with Radix-4 Gradients
The dataset used in this paper is a neural network training dataset with radix-4 gradients.
