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Landslide is a devastating natural disaster with the frequent occurrence and tremendous destructive power. Once it happened, human society, the safety of life and property, and the natural environment would suffer enormous losses. The purpose of landslide research is to reduce landslide occurrence probability through manual intervention to some extent, in which landslide detection is one of the fundamental researches in this field. For state-of-art studies, the hotspot of landslide detection primarily focuses on Deep Learning (DL) and Machine Learning (ML) approaches. In this paper, we summarize the primary works in the field of landslide research firstly. Then the acquisition and usage of landslide data for DL and ML approaches are introduced. Next, the most frequently used evaluation indexes of object detection and image segmentation. Finally, the relevant progress of DL and ML approaches in landslide detection research are reviewed. Meanwhile, the challenges and future research directions in this field are further discussed.

This paper proposes a secure sharing and trading scheme of X-Ray medical image data based on block chain, as it can be used for further scientific research processing. The specific representation includes the following steps: i. The original X-Ray data of medical instruments are transmitted to the cloud platform through the MQTT protocol; ii. The patient information (name, medical card number, etc.) of the image data is encrypted by hashing algorithm to protect privacy; iii. Applying a watermark to the image data; iv. Generating blocks through the consensus mechanism of block chain. The scheme proposed in this paper overcomes the security challenges faced by the traditional cloud-based image data management solution: user privacy disclosure, illegal tampering, and the risk of data being stolen and sold, and realizes a secure transaction system connecting users with data needs, which makes the huge image data on clinical medicine have higher scientific research value.

A dual-channel active laser detection system based on an Avalanche Photo Diode(APD) and a Charge-couple Device(CCD) is designed to effectively detect weak echo signals of "cat-eye" targets and to acquire the intuitive image information of a target area.Firstly,the concept of hardware design is introduced,including the functions and constitution of some modulies and the types of primary assemblies.Then,based on the key problems of designing receiving-magnifying circuit in the APD detection mode,the circuit constitution,working principle and the selection of main parts are discussed,and the match of response spectrum for the CCD and laser is analyzed.Finally,the detection experiments are performed by using typical "cat-eye" targets at different distances.The experimental results show that the echo signal power of the typical "cat-eye" target is 2.87 times that of mirror-like surface at a distance of 550 m in the APD mode;and the echo signal power of a telescope and that of optical window for a laser finder are 2.72 times and 2.31 times those of background at distances of 550 m and 2 500 m in the CCD mode,respectively.The dual-channel active laser detection system can capture the "cat-eye" targets from background and jamming targets easily,which proves the rationality and validity of the proposed system.

An angle-resolved laser detector based on a pair of a non-mechanical scanning Fabry–Perot cavities is described. The differential signal from the two cavities is approximately independent from the polarization of the incident laser beam and it is used to determine the angle of incidence of the beam on the Fabry–Perot cavities. The F–P etalon is made of interferometric filter combination. A laser incident angle sensor experimental platform is built up, and the experiment is carried out with a given laser range finder. When the incident angle is less than 5°, the transmission difference measured by the laser angle sensor is significantly lower than theoretical value, and deviation is more than 10%. When the incident angle is greater than 10°, the deviation is much lower than that of the situation of the incident angle is lower than 10°.

Experimental program is designed to analyze the influence of background radiation on the accuracy of passive ranging based on oxygen spectral absorption; an acousto-optic tunable hyper spectral imaging spectrometer is used as the measuring device and a halogen light as the target. Firstly, the basic principles and experimental program of passive ranging technology based on oxygen absorption are introduced; then the halogen light spectral distribution at different distances during the night is collected using the acousto-optic tunable hyper spectral imaging spectrometer. Oxygen absorption rate is calculated and the relationship model between the oxygen absorption rate and the path is established according to the principle of oxygen spectrum absorption passive ranging. Then the oxygen absorption rate of the target is collected and calculated at the distance of 2360 m for different time. The measuring ranges during the day are solved by the model and the errors are analyzed, the influence of background radiation on the passive ranging is gained finally. Results show that according to the model, the maximum ranging error is 6.74% during the daytime, and the error becomes smaller with the elevation angle of the sun becoming smaller and the background darker. The results give 1.10% ranging error during the nighttime.

In this paper, a new meter band radar superresolution height-finding approach under clutter environments is presented in the presence of multipath, which cascades moving target indication (MTI) method and Forward Backward spatial smooth MUSIC (FBSS-MUSIC) algorithm, the MTI$FBSS-MUSIC approach for short. The numerical simulation analysis of the presented approach is performed and root-mean-square-error of the target height estimation is given. It is demonstrated that clutter suppression method i.e., MTI cascaded superresolution height-finding approach is available for VHF array radar low-angle tracking applications.