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Detection and Classification of Glioblastoma Brain Tumor
Glioblastoma brain tumor detection and segmentation using preprocessed brain MRI images -
SpoC: Spoofing Camera Fingerprints
A GAN-based method to attack both forensic camera model identifiers and GAN detectors. -
Deep Learning-Aided Tabu Search Detection for Large MIMO Systems
The proposed FS-Net detection scheme is a DNN-aided symbol-detection algorithm for MIMO systems. Unlike the prior DetNet and ScNet schemes, the input vector of the FS-Net is... -
Submanifold Sparse Convolutional Networks
Convolutional network are the de-facto standard for analysing spatio-temporal data such as images, videos, 3D shapes, etc. Whilst some of this data is naturally dense (for... -
BENCHMARK ASSESSMENT FOR DEEPSPEED OPTIMIZATION LIBRARY
Deep Learning (DL) models are widely used in machine learning due to their performance and ability to deal with large datasets while producing high accuracy and performance... -
DispersioNET: Joint Inversion of Rayleigh-Wave Multimode Phase Velocity Dispe...
Rayleigh wave dispersion curves have been widely used in near-surface studies, and are primarily inverted for the shear wave (S-wave) velocity profiles. However, the inverse... -
Adversarial Feature Learning
Adversarial Feature Learning -
Target Dataset
The target dataset is a 79 chip target dataset built using the optical imagery generated by Theia, the MRC satellite optical camera. -
Deep-R: Single-shot autofocusing of microscopy images using deep learning
A deep learning-based offline autofocusing framework for microscopy images -
Holy Places Dataset
A dataset of images of holy places (Kaaba, Zamzam, Maqam Ibrahim) for training a deep learning model. -
lfads-torch: A modular and extensible implementation of latent factor analysi...
Latent factor analysis via dynamical systems (LFADS) is an RNN-based variational sequential autoencoder that achieves state-of-the-art performance in denoising high-dimensional... -
DLWP Benchmark
The dataset used for the experiments on Deep Learning Weather Prediction (DLWP) models, comparing and contrasting backbones on Navier-Stokes and Atmospheric Dynamics. -
ResNetX: a more disordered and deeper network architecture
Image classification results on CIFAR-10 and CIFAR-100 benchmarks suggested that our new network architecture performs better than ResNet. -
IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Sho...
Learning to synthesize data has emerged as a promising direction in zero-shot quantization (ZSQ), which represents neural networks by low-bit integer without accessing any of... -
ResNet20 and VGG16
The dataset used in this paper is ResNet20 and VGG16. -
Optimizing for Interpretability in Deep Neural Networks with Tree Regularization
Deep models have advanced prediction in many domains, but their lack of interpretability remains a key barrier to the adoption in many real world applications. This work... -
Generative Adversarial Networks
Generative Adversarial Networks (GANs) consist of two networks: a generator G(z) and a discriminator D(x). The discriminator is trying to distinguish real objects from objects...
