Xerox scanners have been found to randomly alter numbers on documents when reproducing them if a certain combination of image quality and compression setting is used.
Last week came word that the randomly generated crytographic keys used by certain Linux flavors were not so random. Now there's a tool in circulation that can make it easier for attackers to crack the less-than-random keys. Debian, Ubuntu and others have released updates for the key generator. Plus, the SQL injection attack is entering its "third wave," according to IBM.
Three MIT grads this week are celebrating the 10th anniversary of their clever SCIgen program, which randomly generates computer science papers realistic enough to get accepted by sketchy technical conferences and publishers, with a brand new tool designed to poke even more fun at such outfits.
I recently decided, somewhat randomly, to experiment a bit more with social networking. I was on LinkedIn and at some point the service asked me if it could access my Gmail contact list.
Globalization is suffering from economic, financial and political challenges. IT organizations can improve results and mitigate risks by revamping offshore strategies. Implementing globalization no longer creates automatic competitive cost advantage. While nearly all companies have globalization programs, most were created randomly and reactively without strategic consideration. To gain competitive advantage, companies must strategically engineer the integration and synergy from service providers.
Our wireless network includes several consumer-grade 802.11b access points. We've had problems with the network since Day 1 - the connection seems to drop randomly, and then comes back by itself. We don't know what might be causing the interference, or even if interference is the problem. Is there a checklist of things we should go through?
It appears that you are encountering an intermittent issue with your keyboard where the keys "W," "Q," and the Windows key become unresponsive at random
Kinematics Dataset for the NICOL robot (Neuro-inspired Collaborator). Data is intended for Training and Testing of inverse kinematics applications. Contains Training, Test and Validation data for NICOL's right arm. Data for two differently-sized workspaces given. Every sample is a tuple of a uniform randomly sampled robot joint state and the corresponding pose that was calculated with forward kinematics.
Purpose: To demonstrate the feasibility and performance of a fully automated deep learning framework to estimate myocardial strain from short-axis cardiac magnetic resonance tagged images. Methods and Materials: In this retrospective cross-sectional study, 4508 cases from the UK Biobank were split randomly into 3244 training and 812 validation cases, and 452 test cases. Ground truth myocardial landmarks were defined and tracked by manual initialization and correction of deformable image registration using
Multi-label image recognition with partial labels (MLR-PL), in which some labels are known while others are unknown for each multi-label image, aims to train MLR models with partial labels to reduce the annotation cost. Since existing MLR datasets have complete labels, current works propose to randomly drop a certain proportion of positive and negative labels to create partially annotated datasets, and report the results on the known labels proportion of 10% to 90%.
While convolutions are known to be invariant to (discrete) translations, scaling continues to be a challenge and most image recognition networks are not invariant to them. To explore these effects, we have created the Scaled and Translated Image Recognition (STIR) dataset. This dataset contains objects of size $s \in [17, 64]$, each randomly placed in a $64 \times 64$ pixel image.
INSTANCE is a data collection of more than 1.3 million seismic waveforms originating from a selection of about 54,000 earthquakes occurred since 2005 in Italy and surrounding regions and seismic noise recordings randomly extracted from event free time windows of the continuous waveforms archive. The purpose is to provide reference datasets useful to develop and test seismic data processing routines based on machine learning and deep learning frameworks. The primary source of this information is ISIDe (Ital
CIRCO (Composed Image Retrieval on Common Objects in context) is an open-domain benchmarking dataset for Composed Image Retrieval (CIR) based on real-world images from COCO 2017 unlabeled set. It is the first CIR dataset with multiple ground truths and aims to address the problem of false negatives in existing datasets. CIRCO comprises a total of 1020 queries, randomly divided into 220 and 800 for the validation and test set, respectively, with an average of 4.53 ground truths per query.
XA Bin-Picking is a point-cloud dataset comprising both simulated and real-world scenes with three industrial parts. Synthesized scenes consists of 1000 training samples. The test samples are real scenes and the ground
truth instance labels are made manually. There are 20 to
30 identical types of parts randomly piled up in a scene.
Each scene contains about 60,000 boundary points. Each
point in the scene has instance annotations. The parts are
texture-less and have no discernible color. Both of training sa
LayoutLMv2 is an architecture and pre-training method for document understanding. The model is pre-trained with a great number of unlabeled scanned document images from the IIT-CDIP dataset, where some images in the text-image pairs are randomly replaced with another document image to make the model learn whether the image and OCR texts are correlated or not. Meanwhile, it also integrates a spatial-aware self-attention mechanism into the Transformer architecture, so that the model can fully understand the
ERNIE is a transformer-based model consisting of two stacked modules: 1) textual encoder and 2) knowledgeable encoder, which is responsible to integrate extra token-oriented knowledge information into textual information. This layer consists of stacked aggregators, designed for encoding both tokens and entities as well as fusing their heterogeneous features. To integrate this layer of enhancing representations via knowledge, a special pre-training task is adopted for ERNIE - it involves randomly masking to