49,380 Hits in 4.3 sec

Failure detectors as first class objects

P. Felber, X. Defago, R. Guerraoui, P. Oser
1999 Proceedings of the International Symposium on Distributed Objects and Applications  
We plead for an intermediate approach where failure detectors are first class objects.  ...  The various roles of a failure detection service are all represented as first class objects.  ...  Failure Detectors as First Class Objects It is until very recently that the idea of considering failure detection as a first class distributed service has emerged.  ... 
doi:10.1109/doa.1999.794001 dblp:conf/doa/FelberDGO99 fatcat:5d5f633z3jbbdja55nifws5ueu

The Combined Power of Conditions and Information on Failures to Solve Asynchronous Set Agreement

Achour Mostefaoui, Sergio Rajsbaum, Michel Raynal, Corentin Travers
2008 SIAM journal on computing (Print)  
One of the noteworthy features of failure detectors is the modular approach they favor: one can independently, on one side, solve a problem with the help of a particular class of failure detector, and,  ...  On the control side we have the failure detector approach [8], that abstracts away useful failure pattern information, available in common operating scenarios.  ...  detectors.  ... 
doi:10.1137/050645580 fatcat:sqftwep2cvbqhbyul6vizc3uvq

In Search of the Holy Grail: Looking for the Weakest Failure Detector for Wait-Free Set Agreement [chapter]

Michel Raynal, Corentin Travers
2006 Lecture Notes in Computer Science  
This algorithm is based on a leader failure detector class that takes into account the notion of participating processes.  ...  Interestingly, this algorithm enjoys a first class property, namely, design simplicity.  ...  In some sense, this paper looks for a failure detector class that, while being as weak as possible, is as strong as the object O, i.e., a class that allows designing wait-free failure detector-based set  ... 
doi:10.1007/11945529_2 fatcat:vjdaqloeqjdntnz5k5i7jfbfzy

Increasing the Power of the Iterated Immediate Snapshot Model with Failure Detectors [chapter]

Michel Raynal, Julien Stainer
2012 Lecture Notes in Computer Science  
Interestingly, these simulations works for a large family of failure detector classes.  ...  The first states that these models are computationally equivalent for decision tasks. The second states that they are no longer equivalent when both are enriched with the same failure detector.  ...  The failure detector classes C = S x , ✸S x These failure detector classes (introduced in [2] ) extend the classes S and ✸S.  ... 
doi:10.1007/978-3-642-31104-8_20 fatcat:q4yu4t3o2zf6bhpboagjz3qh4i

What's in the Black Box? The False Negative Mechanisms Inside Object Detectors [article]

Dimity Miller, Peyman Moghadam, Mark Cox, Matt Wildie, Raja Jurdak
2022 arXiv   pre-print
In object detection, false negatives arise when a detector fails to detect a target object.  ...  To understand why object detectors produce false negatives, we identify five 'false negative mechanisms', where each mechanism describes how a specific component inside the detector architecture failed  ...  RetinaNet is a popular one-stage anchor-box object detector, and the first of its kind to obtain competitive performance with two-stage detectors [8] . B.  ... 
arXiv:2203.07662v3 fatcat:foiwnblhnfhq5pmoylrbvjmkjm

Robust Tracking Based on Failure Recovery

Daode Zhang, Cheng Xu, Yuanzhong Li
2014 TELKOMNIKA Indonesian Journal of Electrical Engineering  
While suitable for cases when the object is always in the sense and these algorithms always results in failures and can't track back after failure.  ...  While the distance larger then threshold tracking likely to fail, but the latest object model return by detector will reinitialize the tracker.  ...  Detector treats every frame as independent and scans full frame to localize the state of the object.  ... 
doi:10.11591/telkomnika.v12i2.4214 fatcat:sfvmcd3kbjad5ltvkqgia5ib6y

Object Detection for Smart Factory Processes by Machine Learning

Lukas Malburg, Manfred-Peter Rieder, Ronny Seiger, Patrick Klein, Ralph Bergmann
2021 Procedia Computer Science  
Video-based methods such as object detection systems are still in their infancy and rarely used as basis for process monitoring.  ...  Video-based methods such as object detection systems are still in their infancy and rarely used as basis for process monitoring.  ...  The difference between the APs of both failure classes decreases with increasing mAP for failure classes of the detector.  ... 
doi:10.1016/j.procs.2021.04.009 fatcat:wgwllcqvzram3olocmtpjn7au4

Resilience of Autonomous Vehicle Object Category Detection to Universal Adversarial Perturbations [article]

Mohammad Nayeem Teli, Seungwon Oh
2021 arXiv   pre-print
In this work, we bring a fresh perspective on those procedures by evaluating the impact of universal perturbations on object detection at a class-level.  ...  We use Faster-RCNN object detector on images of five different categories: person, car, truck, stop sign and traffic light from the COCO data set, while carefully perturbing the images using Universal  ...  In order to rule out missed detections due to the failure of object detector, we curate the dataset based on the results of the object detector prior to perturbing an image.  ... 
arXiv:2107.04749v1 fatcat:7d7uazo6crgi5cym4jovxj24qm

What Can be Computed in a Distributed System? [chapter]

Michel Raynal
2014 Lecture Notes in Computer Science  
It first presents a few of elements related to distributed computability, and then briefly addresses distributed complexity issues. The style of the paper is voluntarily informal.  ...  In the extreme case where the environment is such that there is no synchrony assumption and the computing entities may commit failures, many problems become impossible to solve (in these cases, a network  ...  As any type of computer science object (e.g., stack or lock), a failure detector class is defined by a set of abstract properties, i.e., independently of the way these properties are implemented.  ... 
doi:10.1007/978-3-642-54848-2_14 fatcat:clpsh3kdv5hh5cvlklobiodh3a

Did You Miss the Sign? A False Negative Alarm System for Traffic Sign Detectors [article]

Quazi Marufur Rahman and Niko Sünderhauf and Feras Dayoub
2019 arXiv   pre-print
The proposed method raises an alarm when it discovers a failure by the object detector to detect a traffic sign.  ...  Object detection is an integral part of an autonomous vehicle for its safety-critical and navigational purposes. Traffic signs as objects play a vital role in guiding such systems.  ...  Our proposed algorithm belongs to the first group of approaches as we use the traffic sign detector to extract important cues to discover the failure of the detector.  ... 
arXiv:1903.06391v1 fatcat:cajp2qc4nzc63hauzrrldx3w2m

On the computability power and the robustness of set agreement-oriented failure detector classes

Achour Mostefaoui, Sergio Rajsbaum, Michel Raynal, Corentin Travers
2008 Distributed computing  
In that sense, it can be seen as a step toward the characterization of the weakest failure detector class that allows solving the k-set agreement problem.  ...  The weakest class of such failure detectors that allow to solve consensus is Ω.  ...  Considering the previous question as a guideline, and base objects that are failure detectors, the paper has investigated three classes of failure detectors, namely, (3S x ) 1≤x≤n , (3ψ y 0≤x≤n ) and (  ... 
doi:10.1007/s00446-008-0064-2 fatcat:33y7m4dqmrd47fmcy6iyrw2mrq

Locks Considered Harmful: A Look at Non-traditional Synchronization [chapter]

Michel Raynal
2008 Lecture Notes in Computer Science  
Then, it is shown how the use of "additional power" such as appropriate failure detectors, or synchronization primitives stronger than read/write operations, allows to bypass the 2p − 1 lower bound.  ...  This paper considers the implementation of concurrent objects in systems prone to asynchrony and process failures.  ...  To that end, a new class of failure detectors (denoted Ω k * ) is first introduced. The parameter k can be seen as measuring the strength of the failure detector.  ... 
doi:10.1007/978-3-540-87785-1_33 fatcat:5334i7ywwbfxxafa3lzgi74she

Probabilistic Failure Detection for Efficient Distributed Storage Maintenance

Jing Tian, Zhi Yang, Wei Chen, Ben Y. Zhao, Yafei Dai
2008 2008 Symposium on Reliable Distributed Systems  
timeout-based detectors using a wide range of parameters.  ...  We conduct extensive simulations based both on synthetic and real traces, and show that Protector closely approximates the performance of a perfect "oracle" failure detector, while significantly outperforming  ...  First, the objectives of the failure detectors are different.  ... 
doi:10.1109/srds.2008.28 dblp:conf/srds/TianYCZD08 fatcat:6wwjo6y6kzdjxm74znzaoz6fsy

Self-supervised object detection from audio-visual correspondence [article]

Triantafyllos Afouras, Yuki M. Asano, Francois Fagan, Andrea Vedaldi, Florian Metze
2022 arXiv   pre-print
We also show that we can align this detector to ground-truth classes with as little as one label per pseudo-class, and show how our method can learn to detect generic objects that go beyond instruments  ...  We tackle the problem of learning object detectors without supervision. Differently from weakly-supervised object detection, we do not assume image-level class labels.  ...  Without using any manual annotations, we learn to detect different objects in images, by first self-labelling boxes and object categories and then using those as targets to teach a detector.  ... 
arXiv:2104.06401v2 fatcat:2ttqidt4cjgbvl4t6dwgztkjty

Measuring the Objectness of Image Windows

B. Alexe, T. Deselaers, V. Ferrari
2012 IEEE Transactions on Pattern Analysis and Machine Intelligence  
In the first, we sample a small number windows according to their objectness probability and give an algorithm to employ them as location priors for modern class-specific object detectors.  ...  In the second application, we use objectness as a complementary score in addition to the class-specific model, which leads to fewer false positives.  ...  While object detectors are specialized for one object class, such as cars or swans, in this paper we define and train a measure of objectness generic over classes.  ... 
doi:10.1109/tpami.2012.28 pmid:22248633 fatcat:njut2gtukzac5c7doismf44gye
« Previous Showing results 1 — 15 out of 49,380 results