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Found 17 papers, 1 papers with code
Synthesizing CTA Image Data for Type-B Aortic Dissection using Stable Diffusion Models
It has been shown that Cardiac CTA images can be successfully generated using using Text to Image (T2I) stable diffusion model.
Derm-T2IM: Harnessing Synthetic Skin Lesion Data via Stable Diffusion Models for Enhanced Skin Disease Classification using ViT and CNN
This study explores the utilization of Dermatoscopic synthetic data generated through stable diffusion models as a strategy for enhancing the robustness of machine learning model training.
Synthetic Speaking Children -- Why We Need Them and How to Make Them
Contemporary Human Computer Interaction (HCI) research relies primarily on neural network models for machine vision and speech understanding of a system user.
A Comparative Study of Image-to-Image Translation Using GANs for Synthetic Child Race Data
The lack of ethnic diversity in data has been a limiting factor of face recognition techniques in the literature.
Will your Doorbell Camera still recognize you as you grow old
This work explores the effect of age and aging on the performance of facial authentication methods.
ChildGAN: Large Scale Synthetic Child Facial Data Using Domain Adaptation in StyleGAN
In this research work, we proposed a novel ChildGAN, a pair of GAN networks for generating synthetic boys and girls facial data derived from StyleGAN2.
Decisive Data using Multi-Modality Optical Sensors for Advanced Vehicular Systems
Optical sensors have played a pivotal role in acquiring real world data for critical applications.
Development, Optimization, and Deployment of Thermal Forward Vision Systems for Advance Vehicular Applications on Edge Devices
In this research work, we have proposed a thermal tiny-YOLO multi-class object detection (TTYMOD) system as a smart forward sensing system that should remain effective in all weather and harsh environmental conditions using an end-to-end YOLO deep learning framework.
Event-based YOLO Object Detection: Proof of Concept for Forward Perception System
The focus is on building efficient state-of-the-art object detection networks with better inference results for fast-moving forward perception using an event camera.
Recurrent Super-Resolution Method for Enhancing Low Quality Thermal Facial Data
The process of obtaining high-resolution images from single or multiple low-resolution images of the same scene is of great interest for real-world image and signal processing applications.
Evaluation of Thermal Imaging on Embedded GPU Platforms for Application in Vehicular Assistance Systems
This study is focused on evaluating the real-time performance of thermal object detection for smart and safe vehicular systems by deploying the trained networks on GPU & single-board EDGE-GPU computing platforms for onboard automotive sensor suite testing.
Object Detection in Thermal Spectrum for Advanced Driver-Assistance Systems (ADAS)
Object detection in thermal infrared spectrum provides more reliable data source in low-lighting conditions and different weather conditions, as it is useful both in-cabin and outside for pedestrian, animal, and vehicular detection as well as for detecting street-signs & lighting poles.
Effectiveness of State-of-the-Art Super Resolution Algorithms in Surveillance Environment
By analyzing and comparing the performance of all the algorithms, a Convolutional Neural Network (CNN) based SR technique using an external dictionary proved to be best by achieving robust face detection accuracy and scoring optimal quantitative metric results under different surveillance conditions.
Generating Thermal Image Data Samples using 3D Facial Modelling Techniques and Deep Learning Methodologies
The same technique is also used on our thermal face data acquired using prototype thermal camera (developed under Heliaus EU project) in an indoor lab environment which is then used for generating synthetic 3D face data along with varying yaw face angles and lastly facial depth map is generated.
Performance Evaluation of Advanced Deep Learning Architectures for Offline Handwritten Character Recognition
The local dataset consists of 62 classes and was created by 40 subjects.
Advanced Deep Learning Methodologies for Skin Cancer Classification in Prodromal Stages
The experimental results demonstrate notable improvement in train and validation accuracy by using the refined version of images of both the networks, however, the Inception-v3 network was able to achieve better validation accuracy thus it was finally selected to evaluate it on test data.
Automatic Lesion Detection System (ALDS) for Skin Cancer Classification Using SVM and Neural Classifiers
Technology aided platforms provide reliable tools in almost every field these days.
