Search Results for author:
Found 7 papers, 3 papers with code
TUR2SQL: A Cross-Domain Turkish Dataset For Text-to-SQL
The field of converting natural language into corresponding SQL queries using deep learning techniques has attracted significant attention in recent years.
A Survey on Automated Diagnosis of Alzheimer's Disease Using Optical Coherence Tomography and Angiography
The paper contains 1) an introduction to the medical background of Alzheimer's Disease and Cognitive Impairment and their diagnosis using OCT and OCTA imaging modalities, 2) a review of various technical proposals for the problem and the sub-problems from an automated analysis perspective, 3) a systematic review of the recent deep learning studies and available OCT/OCTA datasets directly aimed at the diagnosis of Alzheimer's Disease and Cognitive Impairment.
Adaptive Convolution Kernel for Artificial Neural Networks
This paper describes a method for training the size of convolutional kernels to provide varying size kernels in a single layer.
An Adaptive Locally Connected Neuron Model: Focusing Neuron
The tests on convolutional networks revealed that using focusing layers instead of dense layers for the classification of convolutional features may work better in some data sets.
Learning Filter Scale and Orientation In CNNs
Therefore, in a single convolution layer, we can create filters of different scale and orientation that can adapt to small or large features and objects.
Adaptive Gray World-Based Color Normalization of Thin Blood Film Images
This paper presents an effective color normalization method for thin blood film images of peripheral blood specimens.
Assessment of algorithms for mitosis detection in breast cancer histopathology images
The proliferative activity of breast tumors, which is routinely estimated by counting of mitotic figures in hematoxylin and eosin stained histology sections, is considered to be one of the most important prognostic markers.
