Kamil Jeziorek

18 papers B 1Journal 9Unranked 8
YearRankTypeTitle / Venue / Authors
2026 J jnl
Hardware-accelerated graph neural networks: an alternative approach for neuromorphic event-based audio classification and keyword spotting on SoC FPGA.
CoRR
Kamil Jeziorek, Piotr Wzorek, Krzysztof Blachut, Hiroshi Nakano, Manon Dampfhoffer, Thomas Mesquida, Hiroaki Nishi, Thomas Dalgaty, Tomasz Kryjak
2025 — conf
A Model-Driven TTFS Translation for ReLU Neural Networks.
SPA
Michal Michniak, Kamil Jeziorek, Tomasz Kryjak
2025 — conf
Hardware-Accelerated Event-Graph Neural Networks for Low-Latency Time-Series Classification on SoC FPGA.
ARC
Hiroshi Nakano, Krzysztof Blachut, Kamil Jeziorek, Piotr Wzorek, Manon Dampfhoffer, Thomas Mesquida, Hiroaki Nishi, Tomasz Kryjak, Thomas Dalgaty
2025 J jnl
Hardware-Accelerated Event-Graph Neural Networks for Low-Latency Time-Series Classification on SoC FPGA.
CoRR
Hiroshi Nakano, Krzysztof Blachut, Kamil Jeziorek, Piotr Wzorek, Manon Dampfhoffer, Thomas Mesquida, Hiroaki Nishi, Tomasz Kryjak, Thomas Dalgaty
2025 — conf
Hardware-aware Graph Neural Networks prunning for embedded event-based vision.
SPA
Piotr Wzorek, Kamil Jeziorek, Tomasz Kryjak
2025 — conf
Learning from Noise: Enhancing DNNs for Event-Based Vision through Controlled Noise Injection.
CVPR Workshops
Marcin Kowalczyk, Kamil Jeziorek, Tomasz Kryjak
2025 J jnl
Learning from Noise: Enhancing DNNs for Event-Based Vision through Controlled Noise Injection.
CoRR
Marcin Kowalczyk, Kamil Jeziorek, Tomasz Kryjak
2025 B conf
Live Demonstration: Continuous Processing of Event-Data with Graph Convolutional Neural Networks Implemented for SoC FPGA.
FPL
Piotr Wzorek, Kamil Jeziorek, Marcin Kowalczyk, Krzysztof Blachut, Tomasz Kryjak, Marek Gorgon
2025 — conf
Live Demonstration: Real-time event-data processing with Graph Convolutional Neural Networks and SoC FPGA.
CVPR Workshops
Piotr Wzorek, Krzysztof Blachut, Kamil Jeziorek, Tomasz Kryjak
2025 J jnl
Self-Supervised Event Representations: Towards Accurate, Real-Time Perception on SoC FPGAs.
CoRR
Kamil Jeziorek, Tomasz Kryjak
2024 J jnl
Embedded Graph Convolutional Networks for Real-Time Event Data Processing on SoC FPGAs.
CoRR
Kamil Jeziorek, Piotr Wzorek, Krzysztof Blachut, Andréa Pinna, Tomasz Kryjak
2024 — conf
Increasing the Scalability of Graph Convolution for FPGA-Implemented Event-Based Vision: (PhD Forum Paper).
ICFPT
Piotr Wzorek, Kamil Jeziorek, Tomasz Kryjak, Andréa Pinna
2024 J jnl
Increasing the scalability of graph convolution for FPGA-implemented event-based vision.
CoRR
Piotr Wzorek, Kamil Jeziorek, Tomasz Kryjak, Andréa Pinna
2024 — conf
Optimising Graph Representation for Hardware Implementation of Graph Convolutional Networks for Event-Based Vision.
DASIP
Kamil Jeziorek, Piotr Wzorek, Krzysztof Blachut, Andréa Pinna, Tomasz Kryjak
2024 J jnl
Optimising Graph Representation for Hardware Implementation of Graph Convolutional Networks for Event-based Vision.
CoRR
Kamil Jeziorek, Piotr Wzorek, Krzysztof Blachut, Andréa Pinna, Tomasz Kryjak
2023 — conf
Memory-Efficient Graph Convolutional Networks for Object Classification and Detection with Event Cameras.
SPA
Kamil Jeziorek, Andréa Pinna, Tomasz Kryjak
2023 J jnl
Memory-Efficient Graph Convolutional Networks for Object Classification and Detection with Event Cameras.
CoRR
Kamil Jeziorek, Andréa Pinna, Tomasz Kryjak
2022 J jnl
Traffic sign detection and recognition using event camera image reconstruction.
CoRR
Kamil Jeziorek, Tomasz Kryjak
pyproject.toml
← Index pyproject.toml ini 
[tool.black]
line-length = 120
target-version = ['py38']
include = '\.pyi?$'
extend-exclude = '''
/(
  # directories
  \.eggs
  | \.git
  | \.hg
  | \.mypy_cache
  | \.tox
  | \.venv
  | build
  | dist
  | venv
)/
'''

[tool.isort]
profile = "black"
line_length = 120
multi_line_output = 3
include_trailing_comma = true
force_grid_wrap = 0
use_parentheses = true
ensure_newline_before_comments = true

[tool.flake8]
max-line-length = 120
ignore = ["E501", "W503", "E203", "F401"]
exclude = [
    "__pycache__",
    ".git",
    "venv",
    "build",
    "dist",
    "*.egg-info",
]

[tool.pylint.messages_control]
disable = [
    "C0114",  # missing-module-docstring
    "C0115",  # missing-class-docstring
    "C0116",  # missing-function-docstring
    "C0103",  # invalid-name
    "R0903",  # too-few-public-methods
    "R0913",  # too-many-arguments
    "R0914",  # too-many-locals
    "R0915",  # too-many-statements
]

[tool.pylint.format]
max-line-length = 120

# ============================================================================
# Pytest Configuration
# ============================================================================
[tool.pytest.ini_options]
testpaths = ["tests/unit", "tests/integration"]
python_files = ["test_*.py"]
python_classes = ["Test*"]
python_functions = ["test_*"]

# Default options: verbose, show locals on failure, strict markers
addopts = [
    "-v",
    "--strict-markers",
    "--tb=short",
]

# Custom markers for selective test execution
markers = [
    "unit: Pure unit tests - no external deps, no disk I/O, fast (< 1s each)",
    "integration: Integration tests - use real test binaries on disk",
    "slow: Tests that take > 5s (e.g. entropy on large files, full extraction pipelines)",
    "pe: Tests specific to PE binary analysis",
    "elf: Tests specific to ELF binary analysis",
    "macho: Tests specific to Mach-O binary analysis",
    "apk: Tests specific to APK binary analysis",
    "exporters: Tests for database exporters (ClickHouse, Elasticsearch, Print)",
    "dataclass: Tests for dataclass construction and field validation",
    "binja: Tests for Binary Ninja decompiler extractors (mocked, no license needed)",
]