Vision-based semantic segmentation in scene understanding for autonomous driving: Recent achievements, challenges, and outlooks
Scene understanding plays a crucial role in autonomous driving by utilizing sensory data for
contextual information extraction and decision making. Beyond modeling advances, the …
contextual information extraction and decision making. Beyond modeling advances, the …
[HTML][HTML] An empirical survey on explainable ai technologies: Recent trends, use-cases, and categories from technical and application perspectives
M Nagahisarchoghaei, N Nur, L Cummins, N Nur… - Electronics, 2023 - mdpi.com
In a wide range of industries and academic fields, artificial intelligence is becoming
increasingly prevalent. AI models are taking on more crucial decision-making tasks as they …
increasingly prevalent. AI models are taking on more crucial decision-making tasks as they …
Segpgd: An effective and efficient adversarial attack for evaluating and boosting segmentation robustness
Deep neural network-based image classifications are vulnerable to adversarial
perturbations. The image classifications can be easily fooled by adding artificial small and …
perturbations. The image classifications can be easily fooled by adding artificial small and …
Lightweight EfficientNetB3 model based on depthwise separable convolutions for enhancing classification of leukemia white blood cell images
Acute lymphoblastic leukemia (ALL) is a type of leukemia cancer that arises due to the
excessive growth of immature white blood cells (WBCs) in the bone marrow. The ALL rate …
excessive growth of immature white blood cells (WBCs) in the bone marrow. The ALL rate …
Benchmarking image classifiers for physical out-of-distribution examples detection
The rising popularity of deep neural networks (DNNs) in computer vision has raised
concerns about their robustness in the real world. Recent works in this field have well …
concerns about their robustness in the real world. Recent works in this field have well …
Physical adversarial attack meets computer vision: A decade survey
Despite the impressive achievements of Deep Neural Networks (DNNs) in computer vision,
their vulnerability to adversarial attacks remains a critical concern. Extensive research has …
their vulnerability to adversarial attacks remains a critical concern. Extensive research has …
A survey on physical adversarial attack in computer vision
Over the past decade, deep learning has revolutionized conventional tasks that rely on hand-
craft feature extraction with its strong feature learning capability, leading to substantial …
craft feature extraction with its strong feature learning capability, leading to substantial …
On the real-world adversarial robustness of real-time semantic segmentation models for autonomous driving
The existence of real-world adversarial examples (RWAEs)(commonly in the form of
patches) poses a serious threat for the use of deep learning models in safety-critical …
patches) poses a serious threat for the use of deep learning models in safety-critical …
Robustness analysis of video-language models against visual and language perturbations
Joint visual and language modeling on large-scale datasets has recently shown good
progress in multi-modal tasks when compared to single modal learning. However …
progress in multi-modal tasks when compared to single modal learning. However …
Adversarial patch attacks and defences in vision-based tasks: A survey
Adversarial attacks in deep learning models, especially for safety-critical systems, are
gaining more and more attention in recent years, due to the lack of trust in the security and …
gaining more and more attention in recent years, due to the lack of trust in the security and …