Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges.

In he past decade, object detection has achieved significant progress in natural images but not in aerial images, due to the massive variations in the scale and orientation of objects caused by the bird's-eye view of aerial images. More importantly, the lack of large-scale benchmarks has become a major obstacle to the development of object detection in aerial images (ODAI). In this paper, we present a large-scale Dataset of Object deTection in Aerial images (DOTA) and comprehensive baselines for ODAI. The proposed DOTA dataset contains 1,793,658 object instances of 18 categories of oriented-bounding-box annotations collected from 11,268 aerial images. Based on this large-scale and well-annotated dataset, we build baselines covering 10 state-of-the-art algorithms with over 70 configurations, where the speed and accuracy performances of each model have been evaluated. Furthermore, we provide a code library for ODAI and build a website for evaluating different algorithms. Previous challenges run on DOTA have attracted more than 1300 teams worldwide. We believe that the expanded large-scale DOTA dataset, the extensive baselines, the code library and the challenges can facilitate the designs of robust algorithms and reproducible research on the problem of object detection in aerial images.

Pulse Radar with Field-Programmable Gate Array Range Compression for Real Time Displacement and Vibration Monitoring.

This paper aims to present the basic functionality of a radar platform for real time monitoring of displacement and vibration. The real time capabilities make the radar platform useful when live monitoring of targets is required. The system is based on the RF analog front-end of a USRP, and the range compression (time-domain cross-correlation) is implemented on the FPGA included in the USRP. Further processing is performed on the host computer to plot real time range profiles, displacements, vibration frequencies spectra and spectrograms (waterfall plots) for long term monitoring. The system is currently in experimental form and the present paper aims to prove its functionality. The precision of this system is estimated (using the 3σ approximation) at 0.6 mm for displacement measurements and 1.8 mm for vibration amplitude measurements.

On the Use of Normalized Compression Distances for Image Similarity Detection.

This paper investigates the usefulness of the normalized compression distance (NCD) for image similarity detection. Instead of the direct NCD between images, the paper considers the correlation between NCD based feature vectors extracted for each image. The vectors are derived by computing the NCD between the original image and sequences of translated (rotated) versions. Feature vectors for simple transforms (circular translations on horizontal, vertical, diagonal directions and rotations around image center) and several standard compressors are generated and tested in a very simple experiment of similarity detection between the original image and two filtered versions (median and moving average). The promising vector configurations (geometric transform, lossless compressor) are further tested for similarity detection on the 24 images of the Kodak set subject to some common image processing. While the direct computation of NCD fails to detect image similarity even in the case of simple median and moving average filtering in 3 × 3 windows, for certain transforms and compressors, the proposed approach appears to provide robustness at similarity detection against smoothing, lossy compression, contrast enhancement, noise addition and some robustness against geometrical transforms (scaling, cropping and rotation).

The Romanian Acute Heart Failure Syndromes (RO-AHFS) registry.

AIMS: The objective of the RO-AHFS registry was to evaluate the epidemiology, clinical presentation, inpatient management, and hospital course in a population hospitalized for acute heart failure syndromes. METHODS: During a 12-month period, 13 Romanian medical centers enrolled all consecutive patients hospitalized with a primary diagnosis of AHFS. Patients were classified into the following 5 clinical profiles at admission: acute decompensated heart failure, cardiogenic shock, pulmonary edema, right heart failure, and hypertensive heart failure. Statistical significance was assessed using Fisher exact test or the χ(2) test for categorical variables and a 1-way analysis of variance for continuous variables. Independent predictors of in-hospital all-cause mortality (ACM) were identified using a multivariate logistic regression model. RESULTS: A total of 3,224 consecutive patients hospitalized with AHFS were enrolled. The cohort had a mean age of 69.2 ± 11.8 years and 56% were men. The mean left ventricular ejection fraction was 37.7% ± 12.5%. The percentage of patients treated with evidence-based heart failure therapies increased from admission to discharge, but even at discharge, only 56%, 66%, and 54% of patients were on a ß-blocker, an angiotensin-converting enzyme inhibitors or an angiotensin receptor blocker, and a mineralocorticoid receptor antagonist, respectively. In-hospital ACM was 7.7% with substantial variation between sites (4.1%-11.0%). Increasing age, inotrope therapy, the presence of life-threatening ventricular arrhythmias, and elevated baseline blood urea nitrogen were all found to be independent risk factors for in-hospital ACM, whereas elevated systolic blood pressure and baseline treatment with a ß-blocker had a protective effect. CONCLUSIONS: The RO-AHFS study found substantial variation both among sites and between Romania and other European countries. National and regional registries have important clinical implications for patient care and the design and conduct of global clinical trials.

Wavelet-based SAR image despeckling and information extraction, using particle filter.

This paper proposes a new-wavelet-based synthetic aperture radar (SAR) image despeckling algorithm using the sequential Monte Carlo method. A model-based Bayesian approach is proposed. This paper presents two methods for SAR image despeckling. The first method, called WGGPF, models a prior with Generalized Gaussian (GG) probability density function (pdf) and the second method, called WGMPF, models prior with a Generalized Gaussian Markov random field (GGMRF). The likelihood pdf is modeled using a Gaussian pdf. The GGMRF model is used because it enables texture parameter estimation. The prior is modeled using GG pdf, when texture parameters are not needed. A particle filter is used for drawing particles from the prior for different shape parameters of GG pdf. When the GGMRF prior is used, the particles are drawn from prior in order to estimate noise-free wavelet coefficients and for those coefficients the texture parameter is changed in order to obtain the best textural parameters. The texture parameters are changed for a predefined set of shape parameters of GGMRF. The particles with the highest weights represents the final noise-free estimate with corresponding textural parameters. The despeckling algorithms are compared with the state-of-the-art methods using synthetic and real SAR data. The experimental results show that the proposed despeckling algorithms efficiently remove noise and proposed methods are comparable with the state-of-the-art methods regarding objective measurements. The proposed WGMPF preserves textures of the real, high-resolution SAR images well.