3 citations · 6 across the 7 of their papers we have counts for
12 papers
A Large-Scale AIS Dataset from Finnish Water
Debayan Bhattacharya, Ikram Ul Haq, Carlos Pichardo Vicencio +1
This research paper contributes to the maritime research community by introducing a comprehensive AIS dataset from Finnish waters, specifically the Baltic Sea region. AIS data, ini…
Decoding the Multimodal Maze: A Systematic Review on the Adoption of Explainability in Multimodal Attention-based Models
Md Raisul Kibria, Sébastien Lafond, Janan Arslan
Multimodal learning has witnessed remarkable advancements in recent years, particularly with the integration of attention-based models, leading to significant performance gains acr…
CALF: A Conditionally Adaptive Loss Function to Mitigate Class-Imbalanced Segmentation
Bashir Alam, Masa Cirkovic, Mete Harun Akcay +6
Imbalanced datasets pose a considerable challenge in training deep learning (DL) models for medical diagnostics, particularly for segmentation tasks. Imbalance may be associated wi…
Parallel decoder for Low Density Parity Check Codes: A MPSoC study
Sudeep Kanur, Georgios Georgakarakos, Antti Siirilä +4
The near channel performance of Low Density Parity Check Codes (LDPC) has motivated its wide applications. Iterative decoding of LDPC codes provides significant implementation chal…
Identifying gender bias in blockbuster movies through the lens of machine learning
Muhammad Junaid Haris, Aanchal Upreti, Melih Kurtaran +3
The problem of gender bias is highly prevalent and well known. In this paper, we have analysed the portrayal of gender roles in English movies, a medium that effectively influences…
SimuShips -- A High Resolution Simulation Dataset for Ship Detection with Precise Annotations
Minahil Raza, Hanna Prokopova, Samir Huseynzade +2
Obstacle detection is a fundamental capability of an autonomous maritime surface vessel (AMSV). State-of-the-art obstacle detection algorithms are based on convolutional neural net…
Evaluating System Identification Methods for Predicting Thermal Dissipation of Heterogeneous SoCs
Joel Öhrling, Sébastien Lafond, Dragos Truscan
In this paper we evaluate the use of system identification methods to build a thermal prediction model of heterogeneous SoC platforms that can be used to quickly predict the temper…
Online GANs for Automatic Performance Testing
Ivan Porres, Hergys Rexha, Sébastien Lafond
In this paper we present a novel algorithm for automatic performance testing that uses an online variant of the Generative Adversarial Network (GAN) to optimize the test generation…
Enabling Fast Exploration and Validation of Thermal Dissipation Requirements for Heterogeneous SoCs
Joel Öhrling, Dragos Truscan, Sebastien Lafond
The management of the energy consumption and thermal dissipation of multi-core heterogeneous platforms is becoming increasingly important as it can have direct impact on the platfo…
Data Collection and Utilization Framework for Edge AI Applications
Hergys Rexha, Sebastien Lafond
As data being produced by IoT applications continues to explode, there is a growing need to bring computing power closer to the source of the data to meet the response time, power…
Evolutionary computational platform for the automatic discovery of nanocarriers for cancer treatment
Namid Stillman, Igor Balaz, Antisthenis Tsompanas +5
We present the EVONANO platform for the evolution of nanomedicines with application to anti-cancer treatments. EVONANO includes a simulator to grow tumours, extract representative…
On the Verification and Validation of AI Navigation Algorithms
Ivan Porres, Sepinoud Azimi, Sébastien Lafond +3
This paper explores the state of the art on to methods to verify and validate navigation algorithms for autonomous surface ships. We perform a systematic mapping study to find rese…