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Found 33 papers, 5 papers with code
Trustworthy Compression? Impact of AI-based Codecs on Biometrics for Law Enforcement
The loss of detail is qualitatively best seen in fabrics and tattoos images.
Can We Identify Unknown Audio Recording Environments in Forensic Scenarios?
However, in forensic investigations, the candidate locations are case-specific.
LORD: Leveraging Open-Set Recognition with Unknown Data
To mitigate dependency on extensive and costly background datasets, we explore mixup as an off-the-shelf data generation technique.
Point to the Hidden: Exposing Speech Audio Splicing via Signal Pointer Nets
Verifying the integrity of voice recording evidence for criminal investigations is an integral part of an audio forensic analyst's work.
Benchmarking Probabilistic Deep Learning Methods for License Plate Recognition
Such an uncertainty measure allows to detect false predictions, indicating an analyst when not to trust the result of the automated license plate recognition.
Synthesizing Annotated Image and Video Data Using a Rendering-Based Pipeline for Improved License Plate Recognition
The benefits of the proposed data generation pipeline, especially for machine learning scenarios with limited available training data, are demonstrated by an extensive experimental validation in the context of automatic license plate recognition.
3D Rendering Framework for Data Augmentation in Optical Character Recognition
Applying the proposed method, improvements of up to 2. 79 percentage points in terms of Character Error Rate (CER), and up to 7. 88 percentage points in terms of Word Error Rate (WER) are achieved on the subset.
Towards Unconstrained Audio Splicing Detection and Localization with Neural Networks
Freely available and easy-to-use audio editing tools make it straightforward to perform audio splicing.
Forensic License Plate Recognition with Compression-Informed Transformers
Forensic license plate recognition (FLPR) remains an open challenge in legal contexts such as criminal investigations, where unreadable license plates (LPs) need to be deciphered from highly compressed and/or low resolution footage, e. g., from surveillance cameras.
Deep Metric Color Embeddings for Splicing Localization in Severely Degraded Images
In our evaluation, we show that the proposed embedding space outperforms the state of the art on images that have been subject to strong compression and downsampling.
Exploring the Open World Using Incremental Extreme Value Machines
One particular machine learning problem in dynamic environments is open world recognition.
Bayesian Convolutional Neural Networks for Limited Data Hyperspectral Remote Sensing Image Classification
In this work, we use for HSRS image classification a special class of deep neural networks, namely a Bayesian neural network (BNN).
Compliance Challenges in Forensic Image Analysis Under the Artificial Intelligence Act
Under the draft AI act, high-risk AI systems for use in law enforcement are permitted but subject to compliance with mandatory requirements.
Deep learning architectural designs for super-resolution of noisy images
Recent advances in deep learning have led to significant improvements in single image super-resolution (SR) research.
Synthetic Glacier SAR Image Generation from Arbitrary Masks Using Pix2Pix Algorithm
Supervised machine learning requires a large amount of labeled data to achieve proper test results.
The Forchheim Image Database for Camera Identification in the Wild
It consists of more than 23, 000 images of 143 scenes by 27 smartphone cameras, and it allows to cleanly separate image content from forensic artifacts.
Reconstruction of Voxels with Position- and Angle-Dependent Weightings
In this work we first formulate this reconstruction problem in terms of a system matrix and weighting part.
Toward Reliable Models for Authenticating Multimedia Content: Detecting Resampling Artifacts With Bayesian Neural Networks
To this end, we propose to use Bayesian neural networks (BNN), which combine the power of deep neural networks with the rigorous probabilistic formulation of a Bayesian framework.
Merging-ISP: Multi-Exposure High Dynamic Range Image Signal Processing
As such, it is end-to-end trainable, circumvents the use of hand-crafted and potentially complex algorithms, and mitigates error propagation.
FaceForensics++: Learning to Detect Manipulated Facial Images
In particular, the benchmark is based on DeepFakes, Face2Face, FaceSwap and NeuralTextures as prominent representatives for facial manipulations at random compression level and size.
Ranked #1 on
DeepFake Detection
on FaceForensics
ForensicTransfer: Weakly-supervised Domain Adaptation for Forgery Detection
We devise a learning-based forensic detector which adapts well to new domains, i. e., novel manipulation methods and can handle scenarios where only a handful of fake examples are available during training.
A 3-D Projection Model for X-ray Dark-field Imaging
A key step of the reconstruction algorithm is the inversion of a forward projection model.
A Gentle Introduction to Deep Learning in Medical Image Processing
This paper tries to give a gentle introduction to deep learning in medical image processing, proceeding from theoretical foundations to applications.
Toward Bridging the Simulated-to-Real Gap: Benchmarking Super-Resolution on Real Data
One interesting result is that top-performing methods on simulated data may be surpassed by others on real data.
Automatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Images
Both approaches are trained on 1, 968 cells extracted from high resolution EL intensity images of mono- and polycrystalline PV modules.
Segmentation of Photovoltaic Module Cells in Uncalibrated Electroluminescence Images
Automated segmentation of cells is therefore a key step in automating the visual inspection workflow.
Adaptive Quantile Sparse Image (AQuaSI) Prior for Inverse Imaging Problems
Inverse problems play a central role for many classical computer vision and image processing tasks.
FaceForensics: A Large-scale Video Dataset for Forgery Detection in Human Faces
Research on the detection of face manipulations has been seriously hampered by the lack of adequate datasets.
Hyper-Hue and EMAP on Hyperspectral Images for Supervised Layer Decomposition of Old Master Drawings
In this work, we propose an image processing pipeline that operates on hyperspectral images to separate such layers.
GMM-Based Synthetic Samples for Classification of Hyperspectral Images With Limited Training Data
This synthetic data is sampled from a GMM fitted to each class of the limited training data.
Classification Of Hyperspectral Images
General Classification
+1
Image Registration for the Alignment of Digitized Historical Documents
In this work, we conducted a survey on different registration algorithms and investigated their suitability for hyperspectral historical image registration applications.
Sketch Layer Separation in Multi-Spectral Historical Document Images
High-resolution imaging has delivered new prospects for detecting the material composition and structure of cultural treasures.
Benchmarking Super-Resolution Algorithms on Real Data
Therefore, current studies are either evaluated 1) on simulated data or 2) on real data without a pixel-wise ground truth.
