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20162025
most citedEstimating the Prediction Performance of Spatial Models via Spatial k-Fold Cross Validation

208 citations · 414 across the 17 of their papers we have counts for

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Showing 2020Show all

7 papers · 1 filter

cs.CV2020

Asynchronous Corner Tracking Algorithm based on Lifetime of Events for DAVIS Cameras

Sherif A. S. Mohamed, Jawad N. Yasin, Mohammad-Hashem Haghbayan +4

Event cameras, i.e., the Dynamic and Active-pixel Vision Sensor (DAVIS) ones, capture the intensity changes in the scene and generates a stream of events in an asynchronous fashion…

cs.CV2020★ 14 cited

Night vision obstacle detection and avoidance based on Bio-Inspired Vision Sensors

Jawad N. Yasin, Sherif A. S. Mohamed, Mohammad-hashem Haghbayan +4

Moving towards autonomy, unmanned vehicles rely heavily on state-of-the-art collision avoidance systems (CAS). However, the detection of obstacles especially during night-time is s…

cs.CV2020

Dynamic Resource-aware Corner Detection for Bio-inspired Vision Sensors

Sherif A. S. Mohamed, Jawad N. Yasin, Mohammad-hashem Haghbayan +4

Event-based cameras are vision devices that transmit only brightness changes with low latency and ultra-low power consumption. Such characteristics make event-based cameras attract…

cs.RO2020

Dynamic Formation Reshaping Based on Point Set Registration in a Swarm of Drones

Jawad N. Yasin, Sherif A. S. Mohamed, Mohammad-Hashem Haghbayan +4

This work focuses on the formation reshaping in an optimized manner in autonomous swarm of drones. Here, the two main problems are: 1) how to break and reshape the initial formatio…

cs.LG2020★ 1 cited

Utilizing remote sensing data in forest inventory sampling via Bayesian optimization

Jonne Pohjankukka, Sakari Tuominen, Jukka Heikkonen

In large-area forest inventories a trade-off between the amount of data to be sampled and the costs of collecting the data is necessary. It is not always possible to have a very la…

stat.AP2020★ 208 cited

Estimating the Prediction Performance of Spatial Models via Spatial k-Fold Cross Validation

Jonne Pohjankukka, Tapio Pahikkala, Paavo Nevalainen +1

In machine learning one often assumes the data are independent when evaluating model performance. However, this rarely holds in practise. Geographic information data sets are an ex…