On The Coherence of Quantitative Evaluation of Visual Expalantion. - Benjamin Vandersmissen; José Oramas (CoRR, 2023)

Considering Layerwise Importance in the Lottery Ticket Hypothesis. - Benjamin Vandersmissen; José Oramas (CoRR, 2023)

Deep Learning Model Compression for Resource Efficient Activity Recognition on Edge Devices: A Case Study. - Dieter Balemans; Benjamin Vandersmissen; Jan Steckel; Siegfried Mercelis; Philippe Reiter; José Oramas (VISIGRAPP (4): VISAPP, 2024)

Recognizing Actions in High-Resolution Low-Framerate Videos: A Feasibility Study in the Construction Sector. - Benjamin Vandersmissen; Arian Sabaghi; Philippe Reiter; José Oramas (VISIGRAPP (4): VISAPP, 2024)

Twin Network Augmentation: A Novel Training Strategy for Improved Spiking Neural Networks and Efficient Weight Quantization. - Lucas Deckers; Benjamin Vandersmissen; Ing Jyh Tsang; Werner Van Leekwijck; Steven Latré (CoRR, 2024)

On the coherency of quantitative evaluation of visual explanations. - Benjamin Vandersmissen; José Oramas (Comput. Vis. Image Underst., 2024)

Improving Neural Network Accuracy by Concurrently Training with a Twin Network. - Benjamin Vandersmissen; Lucas Deckers; José Oramas M. (ICLR, 2025)