Brave the wind and the waves: Discovering robust and generalizable graph lottery tickets
The training and inference of Graph Neural Networks (GNNs) are costly when scaling up to
large-scale graphs. Graph Lottery Ticket (GLT) has presented the first attempt to accelerate …
large-scale graphs. Graph Lottery Ticket (GLT) has presented the first attempt to accelerate …
Explainable framework for Glaucoma diagnosis by image processing and convolutional neural network synergy: analysis with doctor evaluation
Glaucoma causes blindness in long-time untreated cases. So, its early diagnosis is very
important. Moving from that, there have been lots of Deep Learning oriented studies to …
important. Moving from that, there have been lots of Deep Learning oriented studies to …
Measuring visual walkability perception using panoramic street view images, virtual reality, and deep learning
Measuring perceptions of visual walkability in urban streets and exploring the associations
between the visual features of the street built environment that make walking attractive to …
between the visual features of the street built environment that make walking attractive to …
Endoscopic image classification based on explainable deep learning
D Mukhtorov, M Rakhmonova, S Muksimova, YI Cho - Sensors, 2023 - mdpi.com
Deep learning has achieved remarkably positive results and impacts on medical diagnostics
in recent years. Due to its use in several proposals, deep learning has reached sufficient …
in recent years. Due to its use in several proposals, deep learning has reached sufficient …
Learning pairwise interaction for generalizable deepfake detection
A fast-paced development of DeepFake generation techniques challenge the detection
schemes designed for known type DeepFakes. A reliable Deepfake detection approach …
schemes designed for known type DeepFakes. A reliable Deepfake detection approach …
Towards better explanations of class activation mapping
Increasing demands for understanding the internal behavior of convolutional neural
networks (CNNs) have led to remarkable improvements in explanation methods …
networks (CNNs) have led to remarkable improvements in explanation methods …
Visual explanations via iterated integrated attributions
Abstract We introduce Iterated Integrated Attributions (IIA)-a generic method for explaining
the predictions of vision models. IIA employs iterative integration across the input image, the …
the predictions of vision models. IIA employs iterative integration across the input image, the …
Discovering transferable forensic features for cnn-generated images detection
K Chandrasegaran, NT Tran, A Binder… - European Conference on …, 2022 - Springer
Visual counterfeits (We refer to CNN-generated images as counterfeits throughout this
paper.) are increasingly causing an existential conundrum in mainstream media with rapid …
paper.) are increasingly causing an existential conundrum in mainstream media with rapid …
[HTML][HTML] Method development and application of object detection and classification to Quaternary fossil pollen sequences
R von Allmen, SO Brugger, KD Schleicher… - Quaternary Science …, 2024 - Elsevier
The automation of fossil pollen analysis promises many advantages in handling large
numbers of samples with less resource allocation. However, automation is often obstructed …
numbers of samples with less resource allocation. However, automation is often obstructed …
gscorecam: What objects is clip looking at?
Large-scale, multimodal models trained on web data such as OpenAI's CLIP are becoming
the foundation of many applications. Yet, they are also more complex to understand, test …
the foundation of many applications. Yet, they are also more complex to understand, test …