Found 2908 results, showing the newest relevant preprints. Sort by relevancy only.Update me on new preprints

Unsupervised content-preserving transformation for optical microscopy

We anticipate that our framework will encourage a paradigm shift in training neural networks and democratize deep learning algorithms for optical society. Expand abstract.
28 hours ago
7/10 relevant
bioRxiv

Layer-wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees

To reduce the long training time of large deep neural network (DNN) models, distributed synchronous stochastic gradient descent (S-SGD) is commonly used on a cluster of workers. Expand abstract.
1 day ago
7/10 relevant
arXiv

Semantic Segmentation of Thigh Muscle using 2.5D Deep Learning Network Trained with Limited Datasets

Purpose: We propose a 2.5D deep learning neural network (DLNN) to automatically classify thigh muscle into 11 classes and evaluate its classification accuracy over 2D and 3D DLNN when trained with limited datasets. Expand abstract.
1 day ago
10/10 relevant
arXiv

Distributed Microphone Speech Enhancement based on Deep Learning

Therefore, this study primarily addresses this problem by introducing speech-enhancement (SE) systems based on deep neural networks (DNNs) applied to a distributed microphone architecture. Expand abstract.
3 days ago
8/10 relevant
arXiv

Visualization approach to assess the robustness of neural networks for medical image classification

This means that it may not be possible to rely on deep learning to detect stable regions of interest in this field yet. Expand abstract.
3 days ago
5/10 relevant
arXiv

A Study on various state of the art of the Art Face Recognition System using Deep Learning Techniques

The first part of this review paper basically focuses on deep learning techniques used in face recognition and matching which as improved the accuracy of face recognition technique with training of huge sets of data. Expand abstract.
3 days ago
10/10 relevant
arXiv

Deep Anomaly Detection with Deviation Networks

Existing deep anomaly detection methods, which focus on learning new feature representations to enable downstream anomaly detection methods, perform indirect optimization of anomaly scores, leading to data-inefficient learning and suboptimal anomaly scoring. Expand abstract.
3 days ago
4/10 relevant
arXiv

Automated Human Claustrum Segmentation using Deep Learning Technologies

In recent years, Deep Learning (DL) has shown promising results in conducting AI tasks such as computer vision and image segmentation. Expand abstract.
4 days ago
10/10 relevant
arXiv

A Deep Learning Approach for Robust Corridor Following

We evaluate the performance of our method on this task on a Wheelchair Platform developed at our institute for this purpose. Expand abstract.
4 days ago
7/10 relevant
arXiv

ISP4ML: Understanding the Role of Image Signal Processing in Efficient Deep Learning Vision Systems

Results using ResNets demonstrate that these trends also generalize to deeper networks. Expand abstract.
4 days ago
7/10 relevant
arXiv