The whipworm, Trichuris trichiura, causes trichuriasis in ∼600 million people worldwide, mainly developing countries. Whipworms also infect other animal hosts, including pigs (T. suis), dogs vulpis) and non-human primates, cause disease these which is similar to of humans. Although species are considered be host specific, there has been considerable controversy, over the years, as whether T. trichiura suis same or distinct species. Here, we characterised entire mitochondrial genomes...

<title>Abstract</title> Oriented object detection is one of the most fundamental and challenging tasks in remote sensing, aiming to locate classify objects with arbitrary orientations.Recent advancements deep learning have significantly enhanced capabilities oriented detection.Given rapid development this field, paper presents a comprehensive survey recent advances detection.To be specific, we begin by tracing technical evolution from horizontal higlighting specific challenges, including...

In this paper, we propose a self-calibration approach to stereo cameras with radial distortion from image pairs of common 3D scene. Based on the epipolar constraint in pair, intrinsic and extrinsic parameters are estimated synchronously minimum number nine point correspondences. It is significant within random sample consensus (RANSAC) scheme cope outliers feature matches efficiently robustly. Then inliers pair that have been determined after RANSAC used optimize calibration cameras....

The inertial navigation system (INS) is widely used in spacecraft, missiles, and airplanes for its full autonomy complete information. Skewed measurement unit (IMU) a typical device INS. This IMU of great significance key projects such as manned spacecraft or heavy-lift rockets. Calibration the parameters has always been technology However, calibration skewed difficult to conduct placement sensors complicated model. An all-parameter six-axis proposed this article. error model established....

Video stabilization is a critical step for improving the quality of videos captured by unmanned aerial vehicles. However, complicated scenarios in video and need instantaneously presenting stabilized image posed significant challenges to existing methods. In this work, an instantaneous method vehicles proposed. This new approach serves several purposes: smoothing motion both two-dimensional three-dimensional (3-D) scenes, decreasing lags response, providing users. For each input frame, our...

Automatic and robust matching of multi-modal images can be challenging owing to the nonlinear intensity differences caused by radiometric variations among these images. To address this problem, a novel dense feature descriptor improved similarity measure are proposed for enhancing performance. The is built on voting scheme structure tensor that effectively capture geometric structural properties It not only illumination contrast invariant but also against degradation significant noise....

Cars can appear at any orientations in satellite images, but the widely used traditional histogram of oriented gradient (HOG) features is not rotation‐invariant. Recently, a rotation‐invariant HOG descriptor using Fourier analysis polar coordinators has been proposed and shown good performance; however, it time memory consuming. In this study, authors improve method to present an efficient for car detection images. The first convert spatial convolutions multiplications frequency domain based...

Car detection from unmanned aerial vehicle (UAV) images has become an important research field. However, robust and efficient car is still a challenging problem because of the cars' appearance variations complicated background. We present online cascaded boosting framework with histogram orient gradient (HOG) features for UAV images. First, HOG whole sliding window computed to find primary direction that used estimate car's orientation. The then rotated according estimated orientation, in...

In recent years, remote sensing scene classification has obtained much attention owing to its widespread applications. Nevertheless, existing deep learning-based methods suffer from domain shift. Given a few labeled target samples, semi-supervised adaptation (SSDA) been explored enhance the generalization ability of neural network across domains. However, current SSDA focus on alignment but fail achieve fine-grained category-level feature alignment. this paper, we propose (CFAN), which uses...

Oriented object detection is one of the most fundamental and challenging tasks in remote sensing, aiming to locate classify objects with arbitrary orientations. Recent years have witnessed remarkable progress oriented using deep learning techniques. Given rapid development this field, paper aims provide a comprehensive survey recent advances detection. To be specific, we first review technical evolution from horizontal summarize specific challenges, including feature misalignment, spatial...

When dealing with salient object that contains several regions different appearances, detection can be a difficult task as often only parts of the are highlighted and consistency between is poor. This study tackles this problem by introducing objectness to assist detection. Rather than treating in same manner other low‐level cues (e.g. uniqueness, location etc.) for determination regional saliency values, authors emphasise should also play significant role tuning regions. The integrate...

This paper designs a multiple reflectors based autocollimator, and proposes direct linear solution for three-dimensional (3D) angle measurement with the observation vectors of reflected lights from reflectors. In measuring apparatus, is fixed object to be measured are received by CCD camera, then light spots in image extracted obtain space. Any rotation will induce change lights, which used solve matrix finding Wahba problem quaternion method, 3D obtained decomposing matrix. apparatus can...

The automatic detection of visually salient information from abundant video imagery is crucial, as it plays an important role in surveillance and reconnaissance tasks for Unmanned Aerial Vehicle (UAV). A real-time approach the objects on road, e.g. stationary moving vehicle or people, proposed, which based region segmentation saliency within related domains. Generally, traditional method specifically depends upon additional scene auxiliary thermal IR sensing secondary confirmation. However,...

As a rising navigation technology, vision has many advantages, such as passive measurement, antiinterference, no accumulation of error and comprehensive parameters, etc. It shows promising application prospects in autonomous for UAV. Based on an efficient, reliable accurate scene matching, altimeter 3-D position estimation method are proposed. By matching multiple points between aerial image reference image, it estimates UAV's height according to photogrammetry. To measure velocity, mapless...

A new cross-modal image matching method is proposed to solve the problem that unmanned aerial vehicles (UAVs) are difficult navigate in GPS-free environment and night environment. In this algorithm, infrared or visible matched with satellite image. The process divided into two steps, namely, coarse fine alignment. Based on dense structure features, algorithm can realize position update above 10 Hz a small amount of computation. end-to-end network, alignment align multi-sensor under condition...

Image mosaicking is widely used in Geographic Information Systems (GISs) for large-scale ground surface analysis. However, most existing methods can only be offline processing due to the enormous amounts of computation. In this paper, we propose a novel and practical algorithm real-time infrared video mosaicking. To achieve this, fast template matching based on Sum Cosine Differences (SCD) proposed coarsely match sequential images. The high speed obtained by computing correlation with Fast...

Abstract Domain adaptation for image classification is one of the most fundamental transfer learning tasks and a promising solution to overcome annotation burden. Existing deep adversarial domain approaches imply minimax optimization algorithms, matching global features across domains. However, information conveyed in unlabelled target samples not fully exploited. Here, self‐training are unified an objective function, where neural network parameters pseudo‐labels jointly optimized. The...