Search
Search Results
-
Optimized cross-corpus speech emotion recognition framework based on normalized 1D convolutional neural network with data augmentation and feature selection
Human–computer interaction (HCI) improved via voice detection of emotions. Speech Emotion Recognition (SER) software typically detects the appearance...
-
Evaluation of Point Cloud Data Augmentation for 3D-LiDAR Object Detection in Autonomous Driving
Obstacle detection is an essential component for autonomous vehicles to navigate safely. To address certain limitations of 2D object detection,...
-
Non-linear Vibration Response Analysis of Rolling Bearing for Data Augmentation and Characterization
The bearing fault diagnosis is carried out using nonlinear vibration responses using a proposed framework of VAEGAN–RDCNN. The condition of...
-
Plant Recognition Using Data Augmentation and Convolutional Neural Network
In this paper, the utility of data augmentation in plant recognition is presented. For this, the Swedish Leaf dataset is used. It covers 15 species...
-
Improving Multi-Object Re-identification at Night with GAN Data Augmentation
This study concentrates on a camera-based traffic sensor that measures bicycle, vehicle and pedestrian trips called FlowCube™. To achieve...
-
Generative Adversarial Network for Structural Image Data Augmentation
As mentioned in Sect. 1.3.2 and 2.4, the practical usage of AI in SHM encounters challenges related to the scarcity of labeled data or even...
-
Data Augmentation Method for Improving Object Detection Accuracy of Recumbent Human in Disaster
For this study, we specifically examine object detection methods for finding victims at a facility who are in a lying posture because of injury or...
-
Correction to: Boosting Facial Action Unit Detection with CGAN-Based Data Augmentation
Correction to: Chapter “Boosting Facial Action Unit Detection with CGAN-Based Data Augmentation” in: T. Allahviranloo et al. (eds.), Decision Making...
-
Polyp Segmentation with Deep Ensembles and Data Augmentation
Globally, colorectal cancer is one of the leading causes of mortality. Colonoscopies and the early removal of polys significantly increase the...
-
Object Detection Improvements on Skin Burn Image Data via Data Augmentation and Semi-supervised Learning
Collecting skin burn image data that is treated as medical data is generally restricted to medical practitioners. Labeling them is even more...
-
Data Augmentation for Breast Cancer Mass Segmentation
In medical imaging, a major limitation of supervised Deep Neural Network is the need of large annotated datasets. Current data augmentation methods,...
-
DCGAN for Data Augmentation in Pneumonia Chest X-Ray Image Classification
Major advancement in the field of medical image science is mainly due to deep learning technology, and it has demonstrated good performance in...
-
Custom Data Augmentation Technique (A Deeper Insight)
This paper presents a deeper insight into prior research for the classification of NFRs based on deep learning techniques. This classification system...
-
Forest Fire Detection Method Based on Convolutional Neural Network with Data Augmentation Optimization
Forest fires cause a large number of casualties and property losses worldwide every year, and they cause serious threats and damages to...
-
Data Augmentation Techniques Evaluation on Ultrasound Images for Breast Tumor Segmentation Tasks
A periodic health check with physical examination and assessment of the current health status is among the best approaches to protect your health....
-
Impact of Normalization and Data Augmentation in NER for Algerian Arabic Dialect
Today, social media incorporate a considerable volume and variety of textual data constituting a first source for several NLP applications to take...
-
Evaluating Image Data Augmentation Technique Utilizing Hadamard Walsh Space for Image Classification
Deep neural networks are complex networks that need millions of parameters to be trained and perform well for huge datasets, however result in poor...
-
Data Augmentation and Deep Learning Applied for Traffic Signs Image Classification
Traffic sign recognition is an essential phase for intelligent autonomous driving systems. In this work, we have presented a recognition solution...
-
Practical framework for data-driven RANS modeling with data augmentation
AbstractInspired by the iterative procedure of computing mean fields with known Reynolds stresses (Guo et al., Theor Appl Mech Lett, 2021), we...
-
CAD-based data augmentation and transfer learning empowers part classification in manufacturing
Especially in manufacturing systems with small batches or customized products, as well as in remanufacturing and recycling facilities, there is a...
