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In modern agricultural production, the severity of diseases is an important factor that directly affects the yield and quality of plants. In order to effectively monitor and control the whole production process of crops, it is necessary to clarify not only the types of diseases, but also the severity of diseases. In recent years, the use of Deep Learning (DL) for plant disease species identification has been widely applied. In particular, the application of Convolutional Neural Networks (CNNs) for plant disease images has made breakthrough progress. However, little research has been done on disease severity assessment. This group first traces the mainstream views of existing disease research scholars and accordingly gives various scales for visual assessment of plant disease severity grading. According to the difference of network architecture, then, this study outlines the 16 researches on CNN-based plant disease severity assessment from three aspects of classical CNN framework, improved CNN architecture and CNN-based semantic segmentation network, and the advantages and disadvantages of each research method are compared and analyzed in detail. The common methods of datasets acquisition and the performance evaluation index of CNN models are examined in depth. Finally, this study discusses the major challenges in the practical application of CNN-based plant disease severity assessment methods, and provides feasible research ideas and possible solutions to address these challenges.

Computational ghost imaging has been an interesting topic for the imaging research community. However, low resolution and quality of image have been a major problem inhibiting the application of computational ghost imaging technique. In this work, we develop a chromatic 64 × 64 LED array which provides high-speed structured illumination up to 2.5 MHz for computational ghost imaging. Importantly, rather than using regular Cartesian arrangement which is commonly used in a digital camera’s detection array, the LED chips on chromatic LED array we propose are arranged in a special way we refer to as basket-weave sampling. The experimental results demonstrate that our proposed arrangement outperforms Cartesian arrangement for storing high-frequency information of colored pictures, with averaged root mean squared error (RMSE) reduced by 4.6%. Meanwhile, considering the physical structure of the LED array, we propose a targeted interpolation algorithm for resulting images obtained from the experiment, and results show that our algorithm has lower averaged RMSE by 2% when compared to bilinear algorithm and by 6.4% when compared to bicubic algorithm.

A numerical model of carrier saturation velocity and drain current for the monolayer graphene field effect transistors (GFETs) is proposed by considering the exponential distribution of potential fluctuations in disordered graphene system. The carrier saturation velocity of GFET is investigated by the two-region model, and it is found to be affected not only by the carrier density, but also by the graphene disorder. The numerical solutions of the carrier density and carrier saturation velocity in the disordered GFETs yield clear and physical-based results. The simulated results of the drain current model show good consistency with the reported experimental data.

Firstly Cognitive radio (CR) communication technology is introduced. Then the current research situation of CR-based anti-interference communication are reviewed and analyzed. The two CR-based anti-interference radio structures are given. Then CR-based anti-interference transceivers are introduced and analyzed. Further analysis shows that the future research for CR-based anti-interference radio system should consider the difference between anti-interference user and cognitive user, more environment information interceptions and the combinations of CR and other anti-interference technologies.

This paper proposed a kind of two-dimension partly coherent jamming style against Synthetic Aperture Radar (SAR) named stepped time-delay repeater jamming. Its repeated time-delay increases or deduces by a fixed increment during the irradiation of SAR. The research shows that the presented jamming style can obtain both range and azimuth coherent processing gains when through SAR system. In addition, its SAR imaging output covers some region which could be applied for distributed targets protection. Theoretical analysis and simulation experiments verify its validity.

This work is concerned with developing the blanket jamming technology against SAR based on frequency characteristic. Firstly, the SAR imaging output of the shift frequency jamming style is deduced and analyzed. Then a modified shift frequency jamming to SAR, random Shift frequency jamming (RSFJ), is presented and discussed. The theoretic research and simulation show that the RSFJ is an effective blanket jamming style to SAR with the less jamming power requirement than noise jamming.