Search Results for author:
Found 6 papers, 2 papers with code
Deep learning-based defect detection of metal parts: evaluating current methods in complex conditions
In order to test the performance of state-of-the-art (SOTA) AD methods under conditions of variable spatial orientation, position and distance of multiple objects concerning the camera at different light intensities and with a non-homogeneous background, it is necessary to create a new dataset.
Comparing Normalization Methods for Limited Batch Size Segmentation Neural Networks
Our results show the effectiveness of Instance Normalization in the limited batch size neural network training environment.
Planar 3D Transfer Learning for End to End Unimodal MRI Unbalanced Data Segmentation
We present a novel approach of 2D to 3D transfer learning based on mapping pre-trained 2D convolutional neural network weights into planar 3D kernels.
Towards Robust Voice Pathology Detection
Automatic objective non-invasive detection of pathological voice based on computerized analysis of acoustic signals can play an important role in early diagnosis, progression tracking and even effective treatment of pathological voices.
Voice Pathology Detection Using Deep Learning: a Preliminary Study
This paper describes a preliminary investigation of Voice Pathology Detection using Deep Neural Networks (DNN).
Optimized High Resolution 3D Dense-U-Net Network for Brain and Spine Segmentation
The method has been evaluated on MRI brain 3D volumetric dataset and CT thoracic scan dataset for spine segmentation.
