The image displays four segments of gestures from our dataset.
(a) The video sequence of rotating the wrist down and up as a signal for starting a new gesture.
(b)–(d) Three gestures samples (the triangle, letter b, and letter Z) taken from three different subjects at three different scenes (sitting at a desk, standing indoors, and standing outdoors.). The trajectory of each gesture canbe recognized from the movement of the background objects.
Automatic classification of sensitive content in remote sensing images, such as drug crop sites, is a promising task as it can aid law-enforcement institutions fighting illegal drug dealers worldwide, while, at the same time, it can help monitoring legalized crops in countries that regulate them. However, existing art on detecting drug crops from remote sensing images is limited in some key factors not taking full advantage of the available hyperspectral info for analysis.
The two dataset files contains the experimental results for ICDB DMode and ICDB AMode.
In recent years, researchers have explored human body posture and motion to control robots in more natural ways. These interfaces require the ability to track the body movements of the user in three dimensions. Deploying motion capture systems for tracking tends to be costly and intrusive and requires a clear line of sight, making them ill adapted for applications that need fast deployment. In this article, we use consumer-grade armbands, capturing orientation information and muscle activity, to interact with a robotic system through a state machine controlled by a body motion classifier.
Interventional applications of photoacoustic imaging typically require visualization of point-like targets, such as the small, circular, cross-sectional tips of needles, catheters, or brachytherapy seeds. When these point-like targets are imaged in the presence of highly echogenic structures, the resulting photoacoustic wave creates a reflection artifact that may appear as a true signal. We propose to use deep learning techniques to identify these type of noise artifacts for removal in experimental photoacoustic data.
Machine learning is becoming increasingly important for companies and the scientific community. It allows us to generate solutions for several problems faced by society. In this study, we perform a science mapping analysis on the machine learning research, in order to provide an overview of the scientific work during the last decade in this area and to show trends that could be the basis for future developments in the field of computer science. This study was carried out using the CiteSpace and SciMAT tools based on results from Scopus and Clarivate Web of Science.
These datasets were used to produce the results of the following TMI paper: "3D Quantification of Filopodia in Motile Cancer Cells", Castilla C., et al. (2019). IEEE Transactions on Medical Imaging 38(3):862,872.
These .s2p files contain the S-parameters measured between two on-neck antennas for multiple test subjects acting out four activites. Each files is one trial of measurement, containing 20 seconds of data sampled at 200 Hz.
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Desktops and laptops can be maliciously exploited to violate privacy. In this paper, we consider the daily battle between the passive attacker who is targeting a specific user against a user that may be adversarial opponent. In this scenario, while the attacker tries to choose the best vector attack by surreptitiously monitoring the victim’s encrypted network traffic in order to identify user’s parameters such as the Operating System (OS), browser and apps. The user may use tools such as a Virtual Private Network (VPN) or even change protocols parameters to protect his/her privacy.
For research purposes, the ECG signals were obtained from the PhysioNet service (http://www.physionet.org) from the MIT-BIH Arrhythmia database. The created database with ECG signals is described below. 1) The ECG signals were from 29 patients: 15 female (age: 23-89) and 14 male (age: 32-89). 2) The ECG signals contained 17 classes: normal sinus rhythm, pacemaker rhythm, and 15 types of cardiac dysfunctions (for each of which at least 10 signal fragments were collected). 3) All ECG signals were recorded at a sampling frequency of 360 [Hz] and a gain of 200 [adu / mV].
In this letter, a compact pattern reconfigurable filtering microstrip antenna is presented with broad bandwidth, good selectivity at the passband edge, and flat gain frequency response. The pattern reconfigurable filtering antenna has four resonant modes which can be adjusted independently, three of them are created by multi-mode resonator (MMR) and the other one is by radiator. The four resonant modes are well distributed in desired band and the resonant mode of radiator is located between the first two resonant modes of MMR.
This paper presents an overview of Unidirectional
Loop Metamaterial (ULM) structures and applications. Mimicking
electron spin precession in ferrites using loops with unidirectional
loads (typically transistors), the ULM exhibits all the
fundamental properties of ferrite materials, and represents the
only existing magnetless ferrimagnetic medium. We present here
an extended explanation of ULM physics and unified description
of its component and system applications.
We introduce a novel algorithm for isotropic surface remeshing which progressively eliminates obtuse triangles and improves small angles. The main novelty of the proposed approach is a simple vertex insertion scheme that facilitates the removal of large angles, and a vertex removal operation that improves the distribution of small angles. Combined with other standard local mesh operators, e.g., connectivity optimization and local tangential smoothing, our algorithm is able to remesh a
A microstrip reflectarray antenna is a hybrid design of a reflector antenna and a planar phased array antenna where a feed element illuminates reflecting surface, which can be either flat, slightly curved or a non-uniform plane in order to convert a spherical wave produced by its feed into a plane wave. On the reflecting side of the surface, there might be a series of the printed patch, dipole, loop elements or just a dielectric layer without any power division network.
The dataset provides data for the article " LSTM-based Argument Recommendation for Non-API Methods"
The published sEMG database was captured by the Intelligent System and Biomedical Robotics Group at University of Portsmouth, leaded by Prof. Honghai Liu.
Six subjects were volunteered for data capturing, and the sEMG data were captured in ten separate days. We manually separated the whole database into two parts: training dataset (the first 7 days) and testing dataset(the last 3 days). For each subject, two folders exist, one for training and the other for test.
Visual tracking methods have achieved a successful development in recent years. Especially the Discriminative Correlation Filter (DCF) based methods have significantly advanced the state-of-the-art in tracking. The advancement in DCF tracking performance is predominantly attributed to powerful features and sophisticated online learning formulations. However, it would come to some troubles if the tracker learns the samples indiscriminately.
The IAarticles.csv file has the IAarticles documents collection composed of 66,602 terms (dimensions), 40 documents (objects), and 4 classes (clu, mtx, ont, rif). In the first column it has the name of a document and in the last column it has its class.
The file contains raw data collected from 9 pedestrians. Three of them walked in Track 1, another three walked in Track 2 and the last three walked in Track 3. All the pedestrians ended their walks at the starting point. Track 1 and Track 3 cover a distance of 150.3m. While, the Track covers a distance of 111.4m.
In this paper, we present the Tree Exploration Discovery Protocol (TEDP), proving that shortest paths can be built at the same time that the topology information is gathered, without extra messages compared to LLDP.
A quantitative understanding of how sensory signals are transformed into motor outputs places useful constraints on brain function and helps reveal the brain's underlying computations. Here we present over 8,000 animal hours of behavior recordings to investigate the nematode C. elegans' response to time-varying mechanosensory signals. We use a high-throughput optogenetic assay, video microscopy and automated behavior quantification.
As a precision instrument the microscope is typically used by researchers in criminal investigation, information forensic, biology, metallography, etc. However, the traditional microscope has a dilemma that if it uses the higher magnification, its field of view will be smaller and its depth of field will be more limited. We upgraded a vision measuring system with fully automatic numerical control system as an optical microscope which is used to capture microscopic images.
