activity
20172024
most citedSegmentation of Arterial Walls in Intravascular Ultrasound Cross-Sectional Images Using Extremal Region Selection

58 citations · 258 across the 21 of their papers we have counts for

collaborators

21 papers

cs.CV2024

Textureless Object Recognition: An Edge-based Approach

Frincy Clement, Kirtan Shah, Dhara Pancholi +2

Textureless object recognition has become a significant task in Computer Vision with the advent of Robotics and its applications in manufacturing sector. It has been challenging to…

cs.CV2021★ 54 cited

Subjective and Objective Visual Quality Assessment of Textured 3D Meshes

Jinjiang Guo, Vincent Vidal, Irene Cheng +3

Objective visual quality assessment of 3D models is a fundamental issue in computer graphics. Quality assessment metrics may allow a wide range of processes to be guided and evalua…

eess.IV2020★ 1 cited

Parkinson's Disease Detection with Ensemble Architectures based on ILSVRC Models

Tahjid Ashfaque Mostafa, Irene Cheng

In this work, we explore various neural network architectures using Magnetic Resonance (MR) T1 images of the brain to identify Parkinson's Disease (PD), which is one of the most co…

eess.IV2020★ 2 cited

Parkinson's Disease Detection Using Ensemble Architecture from MR Images

Tahjid Ashfaque Mostafa, Irene Cheng

Parkinson's Disease(PD) is one of the major nervous system disorders that affect people over 60. PD can cause cognitive impairments. In this work, we explore various approaches to…

cs.CV2020★ 10 cited

Adaptive Dithering Using Curved Markov-Gaussian Noise in the Quantized Domain for Mapping SDR to HDR Image

Subhayan Mukherjee, Guan-Ming Su, Irene Cheng

High Dynamic Range (HDR) imaging is gaining increased attention due to its realistic content, for not only regular displays but also smartphones. Before sufficient HDR content is d…

eess.IV2020★ 7 cited

CNN-Based Real-Time Parameter Tuning for Optimizing Denoising Filter Performance

Subhayan Mukherjee, Navaneeth Kamballur Kottayil, Xinyao Sun +1

We propose a novel direction to improve the denoising quality of filtering-based denoising algorithms in real time by predicting the best filter parameter value using a Convolution…