2 citations · 2 across the 6 of their papers we have counts for
6 papers
The Master Key Filters Hypothesis: Deep Filters Are General
Zahra Babaiee, Peyman M. Kiasari, Daniela Rus +1
This paper challenges the prevailing view that convolutional neural network (CNN) filters become increasingly specialized in deeper layers. Motivated by recent observations of clus…
Segmentation of Prostate Tumour Volumes from PET Images is a Different Ball Game
Shrajan Bhandary, Dejan Kuhn, Zahra Babaiee +5
Accurate segmentation of prostate tumours from PET images presents a formidable challenge in medical image analysis. Despite considerable work and improvement in delineating organs…
Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels
Zahra Babaiee, Peyman M. Kiasari, Daniela Rus +1
Recent advances in depthwise-separable convolutional neural networks (DS-CNNs) have led to novel architectures, that surpass the performance of classical CNNs, by a considerable sc…
Neural Echos: Depthwise Convolutional Filters Replicate Biological Receptive Fields
Zahra Babaiee, Peyman M. Kiasari, Daniela Rus +1
In this study, we present evidence suggesting that depthwise convolutional kernels are effectively replicating the structural intricacies of the biological receptive fields observe…
Prediction of Tourism Flow with Sparse Geolocation Data
Julian Lemmel, Zahra Babaiee, Marvin Kleinlehner +5
Modern tourism in the 21st century is facing numerous challenges. Among these the rapidly growing number of tourists visiting space-limited regions like historical cities, museums…
Deep-Learning vs Regression: Prediction of Tourism Flow with Limited Data
Julian Lemmel, Zahra Babaiee, Marvin Kleinlehner +5
Modern tourism in the 21st century is facing numerous challenges. One of these challenges is the rapidly growing number of tourists in space limited regions such as historical city…