SH: Long-tailed classification via spatial constraint sampling, scalable network, and hybrid task.

Long-tailed classification is a significant yet challenging vision task that aims to making the clearest decision boundaries via integrating semantic consistency and texture characteristics. Unlike prior methods, we design spatial constraint sampling and scalable network to bolster the extraction of well-balanced features during training process. Simultaneously, we propose hybrid task to optimize models, which integrates single-model classification and cross-model contrastive learning complementarity to capture comprehensive features.

A New Scene Sensing Model Based on Multi-Source Data from Smartphones.

Smartphones with integrated sensors play an important role in people's lives, and in advanced multi-sensor fusion navigation systems, the use of individual sensor information is crucial. Because of the different environments, the weights of the sensors will be different, which will also affect the method and results of multi-source fusion positioning. Based on the multi-source data from smartphone sensors, this study explores five types of information-Global Navigation Satellite System (GNSS), Inertial Measurement Units (IMUs), cellular networks, optical sensors, and Wi-Fi sensors-characterizing the temporal, spatial, and mathematical statistical features of the data, and it constructs a multi-scale, multi-window, and context-connected scene sensing model to accurately detect the environmental scene in indoor, semi-indoor, outdoor, and semi-outdoor spaces, thus providing a good basis for multi-sensor positioning in a multi-sensor navigation system.

Design and Implementation of Opportunity Signal Perception Unit Based on Time-Frequency Representation and Convolutional Neural Network.

The traditional signal of opportunity (SOP) positioning system is equipped with dedicated receivers for each type of signal to ensure continuous signal perception. However, it causes a low equipment resources utilization and energy waste. With increasing SOP types, problems become more serious.