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Rafael Yela Gunther y Manuel Gamio en Teotihuacan: una historia desconocida para el arte y la arqueología mexicana

Daniel Schávelzon
2012 Anales del Instituto de Investigaciones Estéticas  
Generalmente todos hemos pensado -sin sustento alguno-que, como tantas otras obras en el sitio, el auditorio había sido creado "por" Manuel Gamio, y que la obra concreta debió proyectarla el arquitecto  ...  , Fondo de cultura económica, 1988. 10. aurelio de los Reyes, Manuel Gamio y el cine, México, Universidad nacional autónoma de México, 1991. 11.  ...  Durante los años del gran proyecto antropológico y arqueológico de Manuel Gamio, 1 como es de suponer, además del personal estable en el sitio había jóvenes (y no tan jóvenes) mexicanos y de todo el mundo  ... 
doi:10.22201/iie.18703062e.2008.92.2257 fatcat:k5hfsm6d3raz3ogly4xf7dt7cy

Adversarial Robustness: Softmax versus Openmax [article]

Andras Rozsa, Manuel Günther, Terrance E. Boult
2017 arXiv   pre-print
Deep neural networks (DNNs) provide state-of-the-art results on various tasks and are widely used in real world applications. However, it was discovered that machine learning models, including the best performing DNNs, suffer from a fundamental problem: they can unexpectedly and confidently misclassify examples formed by slightly perturbing otherwise correctly recognized inputs. Various approaches have been developed for efficiently generating these so-called adversarial examples, but those
more » ... ly rely on ascending the gradient of loss. In this paper, we introduce the novel logits optimized targeting system (LOTS) to directly manipulate deep features captured at the penultimate layer. Using LOTS, we analyze and compare the adversarial robustness of DNNs using the traditional Softmax layer with Openmax, which was designed to provide open set recognition by defining classes derived from deep representations, and is claimed to be more robust to adversarial perturbations. We demonstrate that Openmax provides less vulnerable systems than Softmax to traditional attacks, however, we show that it can be equally susceptible to more sophisticated adversarial generation techniques that directly work on deep representations.
arXiv:1708.01697v1 fatcat:hfcopitdlrebvltmzwfe3xp2dy

Reducing Network Agnostophobia [article]

Akshay Raj Dhamija, Manuel Günther, Terrance E. Boult
2018 arXiv   pre-print
Agnostophobia, the fear of the unknown, can be experienced by deep learning engineers while applying their networks to real-world applications. Unfortunately, network behavior is not well defined for inputs far from a networks training set. In an uncontrolled environment, networks face many instances that are not of interest to them and have to be rejected in order to avoid a false positive. This problem has previously been tackled by researchers by either a) thresholding softmax, which by
more » ... ruction cannot return "none of the known classes", or b) using an additional background or garbage class. In this paper, we show that both of these approaches help, but are generally insufficient when previously unseen classes are encountered. We also introduce a new evaluation metric that focuses on comparing the performance of multiple approaches in scenarios where such unseen classes or unknowns are encountered. Our major contributions are simple yet effective Entropic Open-Set and Objectosphere losses that train networks using negative samples from some classes. These novel losses are designed to maximize entropy for unknown inputs while increasing separation in deep feature space by modifying magnitudes of known and unknown samples. Experiments on networks trained to classify classes from MNIST and CIFAR-10 show that our novel loss functions are significantly better at dealing with unknown inputs from datasets such as Devanagari, NotMNIST, CIFAR-100, and SVHN.
arXiv:1811.04110v2 fatcat:5yw56hdxmrdnzcc2oh6kfkvwdu

Estimating genetic kin relationships in prehistoric populations [article]

Jose Manuel Monroy Kuhn, Mattias Jakobsson, Torsten Günther
2017 bioRxiv   pre-print
Archaeogenomic research has proven to be a valuable tool to trace migrations of historic and prehistoric individuals and groups, whereas relationships within a group or burial site have not been investigated to a large extent. Knowing the genetic kinship of historic and prehistoric individuals would give important insights into social structures of ancient and historic cultures. Most archaeogenetic research concerning kinship has been restricted to uniparental markers, while studies using
more » ... -wide information were mainly focused on comparisons between populations. Applications which infer the degree of relationship based on modern-day DNA information typically require diploid genotype data. Low concentration of endogenous DNA, fragmentation and other post-mortem damage to ancient DNA (aDNA) makes the application of such tools unfeasible for most archaeological samples. To infer family relationships for degraded samples, we developed the software READ (Relationship Estimation from Ancient DNA). We show that our heuristic approach can successfully infer up to second degree relationships with as little as 0.1x shotgun coverage per genome for pairs of individuals. We uncover previously unknown relationships among prehistoric individuals by applying READ to published aDNA data from several human remains excavated from different cultural contexts. In particular, we find a group of five closely related males from the same Corded Ware culture site in modern-day Germany, suggesting patrilocality, which highlights the possibility to uncover social structures of ancient populations by applying READ to genome-wide aDNA data.
doi:10.1101/100297 fatcat:7qawqqyp7vc65hzpjvtlegonja

SOBRE LA DISTINCIÓN DE GÜNTHER JAKOBS ENTRE "DERECHO PENAL DEL CIUDADANO" Y "DERECHO PENAL DEL ENEMIGO"

Manuel Jiménez Redondo
2020 Teoría y Derecho  
En el artículo se analiza y se pone en cuestión la distinción entre dos tipos de derecho penal que Günther Jakobs establece en su artículo "Derecho penal del ciudadano y derecho penal del enemigo" (2003  ...  Me voy a referir únicamente al artículo de Jakobs "Derecho penal del ciudadano y derecho penal del enemigo" (en: Günther Jakobs, Manuel Cancio Meliá, Derecho penal del enemigo, editorial Aranzadi, Madrid  ...  A este respecto, pienso que Carl Schmitt es mucho más claro e instructivo que Günther Jakobs.  ... 
doaj:a1d24ef912b1453ebf13304526a2b05f fatcat:txmcw3jmpzarnbtvnb46bug7gy

PARAPH: Presentation Attack Rejection by Analyzing Polarization Hypotheses [article]

Ethan M. Rudd, Manuel Gunther, Terrance E. Boult
2016 arXiv   pre-print
For applications such as airport border control, biometric technologies that can process many capture subjects quickly, efficiently, with weak supervision, and with minimal discomfort are desirable. Facial recognition is particularly appealing because it is minimally invasive yet offers relatively good recognition performance. Unfortunately, the combination of weak supervision and minimal invasiveness makes even highly accurate facial recognition systems susceptible to spoofing via presentation
more » ... attacks. Thus, there is great demand for an effective and low cost system capable of rejecting such attacks.To this end we introduce PARAPH -- a novel hardware extension that exploits different measurements of light polarization to yield an image space in which presentation media are readily discernible from Bona Fide facial characteristics. The PARAPH system is inexpensive with an added cost of less than 10 US dollars. The system makes two polarization measurements in rapid succession, allowing them to be approximately pixel-aligned, with a frame rate limited by the camera, not the system. There are no moving parts above the molecular level, due to the efficient use of twisted nematic liquid crystals. We present evaluation images using three presentation attack media next to an actual face -- high quality photos on glossy and matte paper and a video of the face on an LCD. In each case, the actual face in the image generated by PARAPH is structurally discernible from the presentations, which appear either as noise (print attacks) or saturated images (replay attacks).
arXiv:1605.03124v1 fatcat:ulq4wiiwzvdz3bmiav6m2uhq4a

Toward Open-Set Face Recognition [article]

Manuel Günther, Steve Cruz, Ethan M. Rudd, Terrance E. Boult
2017 arXiv   pre-print
Günther et al.  ...  For unbiased protocols Günther et al. [13] have found that LDA does not improve over simple distance computations in PCA subspace.  ... 
arXiv:1705.01567v2 fatcat:gchycybzbjgqrkdwvymow6p3aa

Liquid co-substrates repower sewage microbiomes [article]

Justus Hardegen, Adriel Latorre-Perez, Cristina Vilanova, Thomas Gunther, Claudia Simeonov, Manuel Porcar, Olaf Luschnig, Christian Abendroth
2018 bioRxiv   pre-print
A range of parameters are known to shape the methanogenic communities of biogas-producing digesters and to strongly influence the amount of biogas produced. In this work, liquid and solid fractions of grass biomass were used separately for semicontinuous batch methanation using sewage sludge as seed sludge. During 6 months of incubation, the amount of input COD was increased gradually, and the underlying methanogenic microbiome was assessed by means of microscopy-based automated cell counting
more » ... d full-length 16S rRNA high-throughput sequencing. In this sense, we prove for the first time the suitability of the ONT TM MinION platform as a monitoring tool for anaerobic digestion systems. According to our results, solid-fed batches were highly unstable at higher COD input concentrations, and kept Methanosaeta spp. -typically associated to sewage sludge- as the majoritary methanogenic archaea. In contrast, liquid-fed batches developed a more stable microbiome, proved enriched in Methanosarcina spp, and resulted in higher methanogenic yield. This work demonstrates the high repowering potential of microbiomes from sewage sludge digesters, and highlight the effectiveness of liquefied substrates for increasing biogas productivity in anaerobic digestions.
doi:10.1101/261339 fatcat:ibjpqmpdjjg5blt4tflgnou2qm

Bob

André Anjos, Laurent El-Shafey, Roy Wallace, Manuel Günther, Christopher McCool, Sébastien Marcel
2012 Proceedings of the 20th ACM international conference on Multimedia - MM '12  
Bob is a free signal processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, Switzerland. The toolbox is designed to meet the needs of researchers by reducing development time and efficiently processing data. Firstly, Bob provides a researcher-friendly Python environment for rapid development. Secondly, efficient processing of large amounts of multimedia data is provided by fast C ++ implementations of identified bottlenecks. The Python
more » ... nvironment is integrated seamlessly with the C ++ library, which ensures the library is easy to use and extensible. Thirdly, Bob supports reproducible research through its integrated experimental protocols for several databases. Finally, a strong emphasis is placed on code clarity, documentation, and thorough unit testing. Bob is thus an attractive resource for researchers due to this unique combination of ease of use, efficiency, extensibility and transparency. Bob is an open-source library and an ongoing community effort.
doi:10.1145/2393347.2396517 dblp:conf/mm/AnjosSWGMM12 fatcat:bvfblgdrprd5rf6ylccpe7kr6u

Estimating genetic kin relationships in prehistoric populations

Jose Manuel Monroy Kuhn, Mattias Jakobsson, Torsten Günther, Francesc Calafell
2018 PLoS ONE  
Archaeogenomic research has proven to be a valuable tool to trace migrations of historic and prehistoric individuals and groups, whereas relationships within a group or burial site have not been investigated to a large extent. Knowing the genetic kinship of historic and prehistoric individuals would give important insights into social structures of ancient and historic cultures. Most archaeogenetic research concerning kinship has been restricted to uniparental markers, while studies using
more » ... -wide information were mainly focused on comparisons between populations. Applications which infer the degree of relationship based on modernday DNA information typically require diploid genotype data. Low concentration of endogenous DNA, fragmentation and other post-mortem damage to ancient DNA (aDNA) makes the application of such tools unfeasible for most archaeological samples. To infer family relationships for degraded samples, we developed the software READ (Relationship Estimation from Ancient DNA). We show that our heuristic approach can successfully infer up to second degree relationships with as little as 0.1x shotgun coverage per genome for pairs of individuals. We uncover previously unknown relationships among prehistoric individuals by applying READ to published aDNA data from several human remains excavated from different cultural contexts. In particular, we find a group of five closely related males from the same Corded Ware culture site in modern-day Germany, suggesting patrilocality, which highlights the possibility to uncover social structures of ancient populations by applying READ to genome-wide aDNA data. READ is publicly available from https://bitbucket.org/tguenther/read.
doi:10.1371/journal.pone.0195491 pmid:29684051 pmcid:PMC5912749 fatcat:fhnsca5prrdideefyd4wyh653a

AFFACT - Alignment-Free Facial Attribute Classification Technique [article]

Manuel Günther and Andras Rozsa and Terrance E. Boult
2017 arXiv   pre-print
Facial attributes are soft-biometrics that allow limiting the search space, e.g., by rejecting identities with non-matching facial characteristics such as nose sizes or eyebrow shapes. In this paper, we investigate how the latest versions of deep convolutional neural networks, ResNets, perform on the facial attribute classification task. We test two loss functions: the sigmoid cross-entropy loss and the Euclidean loss, and find that for classification performance there is little difference
more » ... en these two. Using an ensemble of three ResNets, we obtain the new state-of-the-art facial attribute classification error of 8.00% on the aligned images of the CelebA dataset. More significantly, we introduce the Alignment-Free Facial Attribute Classification Technique (AFFACT), a data augmentation technique that allows a network to classify facial attributes without requiring alignment beyond detected face bounding boxes. To our best knowledge, we are the first to report similar accuracy when using only the detected bounding boxes -- rather than requiring alignment based on automatically detected facial landmarks -- and who can improve classification accuracy with rotating and scaling test images. We show that this approach outperforms the CelebA baseline on unaligned images with a relative improvement of 36.8%.
arXiv:1611.06158v2 fatcat:osdl7lqb3bg5xenyobavkj346i

Hierarchical Road Topology Learning for Urban Map-less Driving [article]

Li Zhang, Faezeh Tafazzoli, Gunther Krehl, Runsheng Xu, Timo Rehfeld, Manuel Schier, Arunava Seal
2021 arXiv   pre-print
The majority of current approaches in autonomous driving rely on High-Definition (HD) maps which detail the road geometry and surrounding area. Yet, this reliance is one of the obstacles to mass deployment of autonomous vehicles due to poor scalability of such prior maps. In this paper, we tackle the problem of online road map extraction via leveraging the sensory system aboard the vehicle itself. To this end, we design a structured model where a graph representation of the road network is
more » ... ated in a hierarchical fashion within a fully convolutional network. The method is able to handle complex road topology and does not require a user in the loop.
arXiv:2104.00084v1 fatcat:jylet54bzzdm3diqh6jn33pipm

Are Facial Attributes Adversarially Robust? [article]

Andras Rozsa, Manuel Günther, Ethan M. Rudd, Terrance E. Boult
2016 arXiv   pre-print
Facial attributes are emerging soft biometrics that have the potential to reject non-matches, for example, based on mismatching gender. To be usable in stand-alone systems, facial attributes must be extracted from images automatically and reliably. In this paper, we propose a simple yet effective solution for automatic facial attribute extraction by training a deep convolutional neural network (DCNN) for each facial attribute separately, without using any pre-training or dataset augmentation,
more » ... d we obtain new state-of-the-art facial attribute classification results on the CelebA benchmark. To test the stability of the networks, we generated adversarial images -- formed by adding imperceptible non-random perturbations to original inputs which result in classification errors -- via a novel fast flipping attribute (FFA) technique. We show that FFA generates more adversarial examples than other related algorithms, and that DCNNs for certain attributes are generally robust to adversarial inputs, while DCNNs for other attributes are not. This result is surprising because no DCNNs tested to date have exhibited robustness to adversarial images without explicit augmentation in the training procedure to account for adversarial examples. Finally, we introduce the concept of natural adversarial samples, i.e., images that are misclassified but can be easily turned into correctly classified images by applying small perturbations. We demonstrate that natural adversarial samples commonly occur, even within the training set, and show that many of these images remain misclassified even with additional training epochs. This phenomenon is surprising because correcting the misclassification, particularly when guided by training data, should require only a small adjustment to the DCNN parameters.
arXiv:1605.05411v3 fatcat:bvdhrmxuyraq7mq6odjrvbbpme

Face Recognition with Disparity Corrected Gabor Phase Differences [chapter]

Manuel Günther, Dennis Haufe, Rolf P. Würtz
2012 Lecture Notes in Computer Science  
We analyze the relative relevance of Gabor amplitudes and phases for face recognition. We propose an algorithm to reliably estimate offset point disparities from phase differences and show that disparitycorrected Gabor phase differences are well suited for face recognition in difficult lighting conditions. The method reaches 74.8% recognition rate on the Lighting set of the CAS-PEAL database and 35.7% verification rate on experiment 2.4 of the FRGC database.
doi:10.1007/978-3-642-33269-2_52 fatcat:cobnxjwusjgsjei66dqea7pd4i

Score calibration in face recognition

Miranti Indar Mandasari, Roy Wallace, Manuel Günther, David A. van Leeuwen, Sébastien Marcel, Rahim Saeidi
2014 IET Biometrics  
An evaluation of the verification and calibration performance of a face recognition system based on inter-session variability modelling is presented. As an extension to calibration through linear transformation of scores, categorical calibration is introduced as a way to include additional information about images for calibration. The cost of likelihood ratio, which is a well-known measure in the speaker recognition field, is used as a calibration performance metric. The results obtained from
more » ... e challenging mobile biometrics and surveillance camera face databases indicate that linearly calibrated face recognition scores are less misleading in their likelihood ratio interpretation than uncalibrated scores. In addition, the categorical calibration experiments show that calibration can be used not only to improve the likelihood ratio interpretation of scores, but also to improve the verification performance of a face recognition system. www.ietdl.org 246 This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/)
doi:10.1049/iet-bmt.2013.0066 fatcat:fcvuayfuqjdajg3pdk2cijtv7a
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