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Found 13 papers, 1 papers with code
Shifting Focus: From Global Semantics to Local Prominent Features in Swin-Transformer for Knee Osteoarthritis Severity Assessment
Conventional imaging diagnostics frequently encounter bottlenecks due to manual inspection, which can lead to delays and inconsistencies.
Quantization Effects on Neural Networks Perception: How would quantization change the perceptual field of vision models?
Neural network quantization is an essential technique for deploying models on resource-constrained devices.
Insights into Classifying and Mitigating LLMs' Hallucinations
The widespread adoption of large language models (LLMs) across diverse AI applications is proof of the outstanding achievements obtained in several tasks, such as text mining, text generation, and question answering.
Automatic diagnosis of knee osteoarthritis severity using Swin transformer
Knee osteoarthritis (KOA) is a widespread condition that can cause chronic pain and stiffness in the knee joint.
Quality evaluation of point clouds: a novel no-reference approach using transformer-based architecture
With the increased interest in immersive experiences, point cloud came to birth and was widely adopted as the first choice to represent 3D media.
An Inter-observer consistent deep adversarial training for visual scanpath prediction
The visual scanpath is a sequence of points through which the human gaze moves while exploring a scene.
PCQA-GRAPHPOINT: Efficients Deep-Based Graph Metric For Point Cloud Quality Assessment
Following the advent of immersive technologies and the increasing interest in representing interactive geometrical format, 3D Point Clouds (PC) have emerged as a promising solution and effective means to display 3D visual information.
Deep-based quality assessment of medical images through domain adaptation
Predicting the quality of multimedia content is often needed in different fields.
A domain adaptive deep learning solution for scanpath prediction of paintings
Cultural heritage understanding and preservation is an important issue for society as it represents a fundamental aspect of its identity.
Self Supervised Scanpath Prediction Framework for Painting Images
In our paper, we propose a novel strategy to learn distortion invariant latent representation from painting pictures for visual attention modelling downstream task.
SalyPath360: Saliency and Scanpath Prediction Framework for Omnidirectional Images
The key setup of our architecture is the simultaneous prediction of the saliency map and a corresponding scanpath for a given stimulus.
SALYPATH: A Deep-Based Architecture for visual attention prediction
Human vision is naturally more attracted by some regions within their field of view than others.
ATSal: An Attention Based Architecture for Saliency Prediction in 360 Videos
The spherical domain representation of 360 video/image presents many challenges related to the storage, processing, transmission and rendering of omnidirectional videos (ODV).
