Overcoming the Limitations of Localization Uncertainty: Efficient & Exact Non-Linear Post-Processing and Calibration

Robustly and accurately localizing objects in real-world environments can be challenging due to noisy data, hardware limitations, and the inherent randomness of physical systems. To account for these factors, existing works estimate the aleatoric uncertainty of object detectors by modeling their localization output as a Gaussian distribution $\mathcal{N}(\mu,\,\sigma^{2})\,$, and training with loss attenuation. We identify three aspects that are unaddressed in the state of the art, but warrant further exploration: (1) the efficient and mathematically sound propagation of $\mathcal{N}(\mu,\,\sigma^{2})\,$ through non-linear post-processing, (2) the calibration of the predicted uncertainty, and (3) its interpretation. We overcome these limitations by: (1) implementing loss attenuation in EfficientDet, and proposing two deterministic methods for the exact and fast propagation of the output distribution, (2) demonstrating on the KITTI and BDD100K datasets that the predicted uncertainty is miscalibrated, and adapting two calibration methods to the localization task, and (3) investigating the correlation between aleatoric uncertainty and task-relevant error sources. Our contributions are: (1) up to five times faster propagation while increasing localization performance by up to 1\%, (2) up to fifteen times smaller expected calibration error, and (3) the predicted uncertainty is found to correlate with occlusion, object distance, detection accuracy, and image quality.Comment: This preprint has not undergone any post-submission improvements or corrections. Accepted to ECML-PKDD 202

On Robustness of Deep Neural Networks: A Comprehensive Study on the Effect of Architecture and Weight Initialization to Susceptibility and Transferability of Adversarial Attacks

Neural network models have shown state of the art performance inseveral applications. However it has been observed that they aresusceptible to adversarial attacks: small perturbations to the inputthat fool a network model into mislabelling the input data. Theseattacks can also transfer from one network model to another, whichraises concerns over their applicability, particularly when there areprivacy and security risks involved. In this work, we conduct a studyto analyze the effect of network architectures and weight initial-ization on the robustness of individual network models as well astransferability of adversarial attacks. Experimental results demon-strate that while weight initialization has no affect on the robustnessof a network model, it does have an affect on attack transferabilityto a network model. Results also show that the complexity of anetwork model as indicated by the total number of parameters andMAC number is not indicative of a network’s robustness to attackor transferability, but accuracy can be; within the same architec-ture, higher accuracy usually indicates a more robust network, butacross architectures there is no strong link between accuracy androbustness

Plasmonic nanomeshes: Their ambivalent role as transparent electrodes in organic solar cells

In this contribution, the optical losses and gains attributed to periodic nanohole array electrodes in polymer solar cells are systematically studied. For this, thin gold nanomeshes with hexagonally ordered holes and periodicities (P) ranging from 202 nm to 2560 nm are prepared by colloidal lithography. In combination with two different active layer materials (P3HT:PC 61 BM and PTB7:PC 71 BM), the optical properties are correlated with the power conversion efficiency (PCE) of the solar cells. A cavity mode is identified at the absorption edge of the active layer material. The resonance wavelength of this cavity mode is hardly defined by the nanomesh periodicity but rather by the absorption of the photoactive layer. This constitutes a fundamental dilemma when using nanomeshes as ITO replacement. The highest plasmonic enhancement requires small periodicities. This is accompanied by an overall low transmittance and high parasitic absorption losses. Consequently, larger periodicities with a less efficient cavity mode, yet lower absorptive losses were found to yield the highest PCE. Nevertheless, ITO-free solar cells reaching ∼77% PCE compared to ITO reference devices are fabricated. Concomitantly, the benefits and drawbacks of this transparent nanomesh electrode are identified, which is of high relevance for future ITO replacement strategies