A comprehensive study on deep learning-based methods for sign language recognition N Adaloglou, T Chatzis, I Papastratis, A Stergioulas, GT Papadopoulos, ... IEEE transactions on multimedia 24, 1750-1762, 2021 | 187 | 2021 |
Intuitive Explanation of Skip Connections in Deep Learning N Adaloglou https://theaisummer.com/skip-connections/, 2020 | 46 | 2020 |
Exploring the Limits of Deep Image Clustering using Pretrained Models N Adaloglou, F Michels, H Kalisch, M Kollmann BMVC 2023, 2023 | 18 | 2023 |
Self-supervision advances morphological profiling by unlocking powerful image representations V Kim, N Adaloglou, M Osterland, FM Morelli, M Halawa, T König, D Gnutt, ... BioRxiv, 2023.04. 28.538691, 2023 | 13* | 2023 |
Deep learning in medical image analysis: a comparative analysis of multi-modal brain-MRI segmentation with 3D deep neural networks A Nikolaos University of Patras, 2019 | 13 | 2019 |
Self-supervised anomaly detection by self-distillation and negative sampling N Rafiee, R Gholamipoor, N Adaloglou, S Jaxy, J Ramakers, M Kollmann International Conference on Artificial Neural Networks, 459-470, 2022 | 12 | 2022 |
Understanding the receptive field of deep convolutional networks N Adaloglou https://theaisummer.com/receptive-field/, 2020 | 11 | 2020 |
Multi-view adaptive graph convolutions for graph classification N Adaloglou, N Vretos, P Daras ECCV 2020, 2020 | 9 | 2020 |
How attention works in deep learning: understanding the attention mechanism in sequence models N Adaloglou, S Karagiannakos https://theaisummer.com/attention/, 2019 | 7 | 2019 |
Adapting Contrastive Language-Image Pretrained (CLIP) Models for Out-of-Distribution Detection N Adaloglou, F Michels, T Kaiser, M Kollmann Transactions on Machine Learning Research, 2835-8856, 2024 | 6* | 2024 |
Best deep cnn architectures and their principles: From alexnet to efficientnet N Adaloglou AI Summer, 2021 | 6* | 2021 |
Transformers in Computer Vision N Adaloglou https://github.com/The-AI-Summer/self-attention-cv, 2021 | 6 | 2021 |
Diffusion models: toward state-of-the-art image generation S Karagiannakos, N Adaloglou https://theaisummer.com/diffusion-models/, 2022 | 4 | 2022 |
Why Multi-head Self Attention Works: Math, Intuitions and 10+ 1 Hidden Insights N Adaloglou https://theaisummer.com/self-attention/, 2021 | 4 | 2021 |
Rethinking cluster-conditioned diffusion models N Adaloglou, T Kaiser, F Michels, M Kollmann arXiv preprint arXiv:2403.00570, 2024 | 3 | 2024 |
How the Vision Transformer (ViT) works in 10 minutes: an image is worth 16x16 words N Adaloglou https://theaisummer.com/vision-transformer/, 2021 | 3 | 2021 |
Scaling Up Deep Clustering Methods Beyond ImageNet-1K N Adaloglou, F Michels, K Senft, D Petrusheva, M Kollmann arXiv preprint arXiv:2406.01203, 2024 | | 2024 |