Search Results for author:
Found 10 papers, 6 papers with code
Transformer-based nowcasting of radar composites from satellite images for severe weather
Weather radar data are critical for nowcasting and an integral component of numerical weather prediction models.
Distributed Online Service Coordination Using Deep Reinforcement Learning
To address these issues, we propose a distributed self-learning service coordination approach using DRL.
Self-Driving Network and Service Coordination Using Deep Reinforcement Learning
While this typically works well for the considered scenario, the models often rely on unrealistic assumptions or on knowledge that is not available in practice (e. g., a priori knowledge).
Machine Learning for Dynamic Resource Allocation in Network Function Virtualization
To solve this problem, we train machine learning models on real VNF data, containing measurements of performance and resource requirements.
Counting Fish and Dolphins in Sonar Images Using Deep Learning
We propose a novel approach to calculating fish abundance using deep learning for fish and dolphin estimates from sonar images taken from the back of a trolling boat.
The Softwarised Network Data Zoo
To this end, we introduce the "softwarised network data zoo" (SNDZoo), an open collection of software networking data sets aiming to streamline and ease machine learning research in the software networking domain.
Similarity Learning Networks for Animal Individual Re-Identification -- Beyond the Capabilities of a Human Observer
Without any species-specific modifications, our results demonstrate that similarity comparison networks can reach a performance level beyond that of humans for the task of animal re-identification.
Past, Present, and Future Approaches Using Computer Vision for Animal Re-Identification from Camera Trap Data
The ability of a researcher to re-identify (re-ID) an individual animal upon re-encounter is fundamental for addressing a broad range of questions in the study of ecosystem function, community and population dynamics, and behavioural ecology.
Deep Learning Object Detection Methods for Ecological Camera Trap Data
Recent advances in the field of deep learning for object detection show promise towards automating the analysis of camera trap images.
Fast Exact k-Means, k-Medians and Bregman Divergence Clustering in 1D
We present all the existing work that had been overlooked and compare the various solutions theoretically.
