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Found 15 papers, 2 papers with code
Multimodal Ensemble with Conditional Feature Fusion for Dysgraphia Diagnosis in Children from Handwriting Samples
In recent years, researchers have increasingly explored machine learning methods to support the diagnosis of dysgraphia based on offline and online handwriting.
Advancing Histopathology-Based Breast Cancer Diagnosis: Insights into Multi-Modality and Explainability
The purpose of this review is to explore the burgeoning field of multimodal techniques, particularly the fusion of histopathology images with non-image data.
Classification of Dysarthria based on the Levels of Severity. A Systematic Review
Specifically, this review will focus on determining the most effective set and type of features that can be used for automatic patient classification and evaluating the best AI techniques for this purpose.
A Novel Deep Learning Technique for Morphology Preserved Fetal ECG Extraction from Mother ECG using 1D-CycleGAN
It can also accurately produce the estimation of fetal heart rate and R-R interval with an error of 0. 25% and 0. 27%, respectively.
3D objects and scenes classification, recognition, segmentation, and reconstruction using 3D point cloud data: A review
Nevertheless, working with this emerging type of data has been a challenging task for objects representation, scenes recognition, segmentation, and reconstruction.
Deep Transfer Learning for Automatic Speech Recognition: Towards Better Generalization
Moreover, DL techniques and machine learning (ML) approaches in general, hypothesize that training and testing data come from the same domain, with the same input feature space and data distribution characteristics.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Automated Systems For Diagnosis of Dysgraphia in Children: A Survey and Novel Framework
The few available artificial intelligence-powered screening systems for dysgraphia relies on the distinctive features of handwriting from the corresponding images. This work presents a review of the existing automated dysgraphia diagnosis systems for children in the literature.
Backbones-Review: Feature Extraction Networks for Deep Learning and Deep Reinforcement Learning Approaches
These networks are exploited for feature extraction or at the beginning of any DL model which is named backbones.
Panoptic Segmentation: A Review
Image segmentation for video analysis plays an essential role in different research fields such as smart city, healthcare, computer vision and geoscience, and remote sensing applications.
VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results
Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint.
An encoder-decoder-based method for COVID-19 lung infection segmentation
But the challenges of these features such as the quality of the image and infection characteristics limitate the effectiveness of these features.
Image inpainting: A review
Furthermore, collect a list of the available datasets and discuss these in our paper.
A Novel Approach for Robust Multi Human Action Recognition and Summarization based on 3D Convolutional Neural Networks
For that, this paper proposes a new technic for multiple human action recognition and summarization for surveillance videos.
Colorectal cancer diagnosis from histology images: A comparative study
Moreover, we conduct quantitative comparative evaluations among the traditional methods, transfer learning-based methods and the proposed adaptive approach for the particular task of cancer detection and identification from scarce and low-resolution histology images.
Composition Loss for Counting, Density Map Estimation and Localization in Dense Crowds
With multiple crowd gatherings of millions of people every year in events ranging from pilgrimages to protests, concerts to marathons, and festivals to funerals; visual crowd analysis is emerging as a new frontier in computer vision.
Ranked #15 on
Crowd Counting
on UCF-QNRF
