Semantic segmentation is a scene understanding task at the heart of
safe...
In this paper, we propose a model-based characterization of neural netwo...
Visual explanations are logical arguments based on visual features that
...
Learning representations that clearly distinguish between normal and abn...
Traffic signs are critical for maintaining the safety and efficiency of ...
In this paper, we utilize weight gradients from backpropagation to
chara...
Abnormalities in pupillary light reflex can indicate optic nerve disorde...
In this paper, we introduce a portable eye imaging device denoted as
lab...
State-of-the-art algorithms successfully localize and recognize traffic ...
In this paper, we investigate the reliability of online recognition
plat...
In this paper, we generate and control semantically interpretable filter...
An average healthy person does not perceive the world in just black and
...
In this paper, we train independent linear decoder models to estimate th...
In this paper, we introduce an adaptive unsupervised learning framework,...
The process of quantifying image quality consists of engineering the qua...
In this paper, we analyze the effect of boosting in image quality assess...
We propose a rate-distortion optimization method for 3D videos based on
...
The 3D video quality metric (3VQM) was proposed to evaluate the temporal...
Objective metrics model image quality by quantifying image degradations ...
An average observer perceives the world in color instead of black and wh...
This paper proposes a biologically-inspired low-level
spatiochromatic-mo...
This paper presents a full-reference image quality estimator based on SI...
In this paper, we introduce a large-scale, controlled, and multi-platfor...
This paper presents a full-reference image quality estimator based on co...
Robust and reliable traffic sign detection is necessary to bring autonom...
In this paper, we analyze the statistics of error signals to assess the
...
In this paper, we investigate the robustness of traffic sign recognition...