Traffic sign detection and recognition using event camera image reconstruction. - Kamil Jeziorek; Tomasz Kryjak (CoRR, 2022)

Memory-Efficient Graph Convolutional Networks for Object Classification and Detection with Event Cameras. - Kamil Jeziorek; Andréa Pinna 001; Tomasz Kryjak (SPA, 2023)

Optimising Graph Representation for Hardware Implementation of Graph Convolutional Networks for Event-Based Vision. - Kamil Jeziorek; Piotr Wzorek; Krzysztof Blachut; Andréa Pinna 001; Tomasz Kryjak (DASIP, 2024)

Increasing the Scalability of Graph Convolution for FPGA-Implemented Event-Based Vision: (PhD Forum Paper). - Piotr Wzorek; Kamil Jeziorek; Tomasz Kryjak; Andréa Pinna 001 (ICFPT, 2024)

Embedded Graph Convolutional Networks for Real-Time Event Data Processing on SoC FPGAs. - Kamil Jeziorek; Piotr Wzorek; Krzysztof Blachut; Andréa Pinna 001; Tomasz Kryjak (CoRR, 2024)

Increasing the scalability of graph convolution for FPGA-implemented event-based vision. - Piotr Wzorek; Kamil Jeziorek; Tomasz Kryjak; Andréa Pinna 001 (CoRR, 2024)

Hardware-Accelerated Event-Graph Neural Networks for Low-Latency Time-Series Classification on SoC FPGA. - Hiroshi Nakano; Krzysztof Blachut; Kamil Jeziorek; Piotr Wzorek; Manon Dampfhoffer; Thomas Mesquida; Hiroaki Nishi; Tomasz Kryjak; Thomas Dalgaty (ARC, 2025)

Learning from Noise: Enhancing DNNs for Event-Based Vision through Controlled Noise Injection. - Marcin Kowalczyk; Kamil Jeziorek; Tomasz Kryjak (CVPR Workshops, 2025)

Live Demonstration: Real-time event-data processing with Graph Convolutional Neural Networks and SoC FPGA. - Piotr Wzorek; Krzysztof Blachut; Kamil Jeziorek; Tomasz Kryjak (CVPR Workshops, 2025)

Self-Supervised Event Representations: Towards Accurate, Real-Time Perception on SoC FPGAs. - Kamil Jeziorek; Tomasz Kryjak (CoRR, 2025)