59 citations · 282 across the 64 of their papers we have counts for
7 papers · 1 filter
Learning to ignore: rethinking attention in CNNs
Firas Laakom, Kateryna Chumachenko, Jenni Raitoharju +2
Recently, there has been an increasing interest in applying attention mechanisms in Convolutional Neural Networks (CNNs) to solve computer vision tasks. Most of these methods learn…
Robust channel-wise illumination estimation
Firas Laakom, Jenni Raitoharju, Jarno Nikkanen +2
Recently, Convolutional Neural Networks (CNNs) have been widely used to solve the illuminant estimation problem and have often led to state-of-the-art results. Standard approaches…
Automatic Main Character Recognition for Photographic Studies
Mert Seker, Anssi Männistö, Alexandros Iosifidis +1
Main characters in images are the most important humans that catch the viewer's attention upon first look, and they are emphasized by properties such as size, position, color satur…
Continual 3D Convolutional Neural Networks for Real-time Processing of Videos
Lukas Hedegaard, Alexandros Iosifidis
We introduce Continual 3D Convolutional Neural Networks (Co3D CNNs), a new computational formulation of spatio-temporal 3D CNNs, in which videos are processed frame-by-frame rather…
Analysis of voxel-based 3D object detection methods efficiency for real-time embedded systems
Illia Oleksiienko, Alexandros Iosifidis
Real-time detection of objects in the 3D scene is one of the tasks an autonomous agent needs to perform for understanding its surroundings. While recent Deep Learning-based solutio…
Single-Layer Vision Transformers for More Accurate Early Exits with Less Overhead
Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis
Deploying deep learning models in time-critical applications with limited computational resources, for instance in edge computing systems and IoT networks, is a challenging task th…
Improving the Accuracy of Early Exits in Multi-Exit Architectures via Curriculum Learning
Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis
Deploying deep learning services for time-sensitive and resource-constrained settings such as IoT using edge computing systems is a challenging task that requires dynamic adjustmen…