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High-resolution remote sensing images possess a wealth of semantic information. However, these images often contain objects of different sizes and distributions, which make the semantic segmentation task challenging. In this paper, a bidirectional feature fusion network (BFFNet) is designed to address this challenge, which aims at increasing the accurate recognition of surface objects in order to effectively classify special features.

There are two main crucial elements in BFFNet. Firstly, the mean-weighted module (MWM) is used to obtain the key features in the main network. Secondly, the proposed polarization enhanced branch network performs feature extraction simultaneously with the main network to obtain different feature information. The authors then fuse these two features in both directions while applying a cross-entropy loss function to monitor the network training process. Finally, BFFNet is validated on two publicly available datasets, Potsdam and Vaihingen.

In this paper, a quantitative analysis method is used to illustrate that the proposed network achieves superior performance of 2–6%, respectively, compared to other mainstream segmentation networks from experimental results on two datasets. Complete ablation experiments are also conducted to demonstrate the effectiveness of the elements in the network. In summary, BFFNet has proven to be effective in achieving accurate identification of small objects and in reducing the effect of shadows on the segmentation process.

The originality of the paper is the proposal of a BFFNet based on multi-scale and multi-attention strategies to improve the ability to accurately segment high-resolution and complex remote sensing images, especially for small objects and shadow-obscured objects.

Laser-based measurement techniques offer various advantages over conventional measurement techniques, such as no-destructive, no-contact, fast and long measuring distance. In cooperative laser ranging systems, it’s crucial to extract center coordinates of retroreflectors to accomplish automatic measurement. To solve this problem, this paper aims to propose a novel method.

We propose a method using Mask RCNN (Region Convolutional Neural Network), with ResNet101 (Residual Network 101) and FPN (Feature Pyramid Network) as the backbone, to localize retroreflectors, realizing automatic recognition in different backgrounds. Compared with two other deep learning algorithms, experiments show that the recognition rate of Mask RCNN is better especially for small-scale targets. Based on this, an ellipse detection algorithm is introduced to obtain the ellipses of retroreflectors from recognized target areas. The center coordinates of retroreflectors in the camera coordinate system are obtained by using a mathematics method.

To verify the accuracy of this method, an experiment was carried out: the distance between two retroreflectors with a known distance of 1,000.109 mm was measured, with 2.596 mm root-mean-squar error, meeting the requirements of the coarse location of retroreflectors.

The research limitations/implications are as follows: (i) As the data set only has 200 pictures, although we have used some data augmentation methods such as rotating, mirroring and cropping, there is still room for improvement in the generalization ability of detection. (ii) The ellipse detection algorithm needs to work in relatively dark conditions, as the retroreflector is made of stainless steel, which easily reflects light.

The originality/value of the article lies in being able to obtain center coordinates of multiple retroreflectors automatically even in a cluttered background; being able to recognize retroreflectors with different sizes, especially for small targets; meeting the recognition requirement of multiple targets in a large field of view and obtaining 3 D centers of targets by monocular model-based vision.

Successive Approximation Register-Analog to Digital Converter (SAR-ADC) has been achieved notable technological advancement since the past couple of decades. However, it’s not accurate in terms of size, energy, and time consumption. Many projects proposed to make it energy efficient and time-efficient. Such designs are unable to deliver two parallel outputs.

To this end, this study introduced an ultra-low-power circuitry for the two blocks (bootstrap and comparator) of 11-bit SAR-ADC. The bootstrap has three sub-parts: back-bone, left-wing and right-wing, named as bat-bootstrap. The comparator block has a circuitry of the two comparators and an amplifier, named as comp-lifier. In a bat-bootstrap, the authors plant two capacitors in the back-bone block to avoid the patristic capacitance. The switching system of the proposed design highly synchronized with the short pulses of the clocks for high accuracy. This study simulates the proposed circuits using a built-in Cadence 90 nm Complementary Metal Oxide Semiconductor library.

The results suggested that the response time of two bat-bootstrap wings and comp-lifier are 80 ns, 120 ns, and 90 ns, respectively. The supply voltage is 0.7 V, wherever the power consumption of bat-bootstrap, comp-lifier and SAR-ADC are 0.3561µW, 0.257µW and 35.76µW, respectively. Signal to Noise and Distortion Ratio is 65 dB with 5 MHz frequency and 25 KS/s sampling rate. The input referred noise of the amplifier and two comparators are 98µVrms, 224µVrms and 224µVrms, respectively.

Two basic circuit blocks for SAR-ADC are introduced, which fulfill the duality approach and delivered two outputs with highly synchronized clock pulses. The circuit sharing concept introduced for the high performance SAR-ADCs.

Laser absolute distance measurement has the characteristics of high precision, wide range and non-contact. In laser ranging system, tracking and aiming measurement point is the precondition of automatic measurement. To solve this problem, this paper aims to propose a novel method.

For the central point of the hollow angle coupled mirror, this paper proposes a method based on correlation filtering and ellipse fitting. For non-cooperative target points, this paper proposes an extraction method based on correlation filtering and feature matching. Finally, a visual tracking and aiming system was constructed by combining the two-axis turntable, and experiments were carried out.

The target tracking algorithm has an accuracy of 91.15% and a speed of 19.5 frames per second. The algorithm can adapt to the change of target scale and short-term occlusion. The mean error and standard deviation of the center point extraction of the hollow Angle coupling mirror are 0.20 and 0.09 mm. The mean error and standard deviation of feature points matching for non-cooperative target were 0.06 mm and 0.16 mm. The visual tracking and aiming system can track a target running at a speed of 0.7 m/s, aiming error mean is 1.74 pixels and standard deviation is 0.67 pixel.

The results show that this method can achieve fast and high precision target tracking and aiming and has great application value in laser ranging.

There are many types of the ADCs implemented in the mobile and wireless devices. Most of these devices are battery operated and operational at low input voltage. SAR ADC is popular for its low power operations and simple architecture. Scientists are still working to make its working faster under the same low power area. There are many SAR-ADC implemented in the past two decades, but still, there is a big room for dual SAR-ADC.

The authors are presenting a dual SAR-ADC with a smaller number of components and blocks. The proposed ultra-low-power circuit of the SAR-ADC consists of four major blocks, which include Bee-bootstrap, Spider-Latch dual comparator, dual SAR-logic and dual digital to analog converter. The authors have used the 90-nm CMOS library for the construction of the design.

The power breaks down of the comparator are dramatically improved from 0.006 to 0.003 uW. The ultimate design has 5 MHz operating frequency with 25 KS/s sampling frequency. The supply voltage is 1.2 V with 35.724 uW power consumption. Signal-to-noise and distortion ratio and spurious-free dynamic range are 65 and 84 dB, respectively. The Walden's figure of merits calculated 7.08 fj/step.

The authors are proposing two-in-one circuit for SAR-ADC named as “dual SAR-ADC”, which obeys the basic equation of duality, derived and proved under the heading of proposed solution. It shows a clear difference between the performance of two circuit-based ADC and one dual circuit ADC. The number of components is reduced by sharing the work load of some key components.

Presents the principles of thirty six Chinese classical strategies which includes strategies for attack, strength, confrontation, confusion, gaining ground and desperate situations. Applies these to strategic planning and marketing rather than the traditional use on battlefields. Uses anecdotal evidence to give examples and suggests that they are relevant to many other business areas.

This study examines how informal business networks achieve marketing goals in socially uncertain contexts. Drawing from multiple historical sources, Shangbangs, a type of business network that thrived in pre-1949 China, are analyzed.

The Critical Historical Research Method (CHRM) undergirds a study of Shangbangs’ historicity (i.e. their socio-historically embedded multiplicity, including organizational forms, activities and connotations.

As informal regional, professional, project-based, special-product-based or mixed marketing networks, Shangbangs relied on “flexible specialization” and coupled multiple business needs to market goods and services, business organizations, specific social values and, when necessary, to debrand business rivals.

This analysis extends theories about marketing networks by probing their subtypes, diverse marketing activities, multipronged channels and relationship building with social entities (including underground societies, business associations and guilds) in response to pre-1949 China’s market uncertainties. Substantiating an alternative approach to “flexible specialization” and marketing innovations within the pre-1949 Chinese economy shows how a parallel theoretical framework can complement western-based marketing theories.

This first comprehensive analysis of Shangbangs, an innovative historical Chinese marketing network outside the conventional market-corporate dichotomy, can inform theory building for marketing strategy-making and management conditioned by social contexts.