KEYWORDS: Transformers, Pose estimation, Feature extraction, Visualization, Education and training, Feature fusion, RGB color model, Human vision and color perception, Image processing, Performance modeling
Despite the significant progress achieved by visual Transformers, there are still some limitations that need to be addressed in human pose estimation. Firstly, Transformer lacks CNN’s inductive bias and local feature attention capabilities, which require extensive training data and iterations to achieve satisfactory results. Therefore, we propose a hybrid network that combines convolutional and Transformer. Besides, to address the recognition of human body images at different scales, we established a Transformer pyramid structure, which achieves recognition of human body images at different scales through progressive reduction of the input resolution. Specifically, our algorithm achieves an accuracy of 77.3% with a computational complexity of 19.6 GFLOPs. Compared to traditional direct regression methods, our algorithm considerably enhances detection accuracy while reducing the training complexity and significantly increasing the detection speed compared to traditional Transformer methods.
As ecological priority has become a central theme of current development, the Yangtze River Delta Eco-Green Integrated Development Demonstration Zone is contributing as a guiding model to China’s ecological and green integrated development. From a perspective of ecosystem service functions, in particular, geographical locations and land habitats for animals and plants, we provide an analysis of the aforementioned Demonstration Zone regarding the distribution, connectivity, and accessibility of its ecological sources, in order to select strategic zones and optimize ecological spaces, from remote sensing imagery. Our analysis was based on the evolution of the ecological base and the Sources-Resistance Surface-Corridors framework integrating local conditions and characteristics. Through navigating remote sensing images of the target area, results indicated that a considerable change occurred in the plant community in the Demonstration Zone over the recent three decades, caused by the severely damaged wetland ecosystem and the limited communications among species due to urban expansion. In addition, the study revealed poor connectivity among the ecological and geographical sources. Accordingly, we propose a set of measures to avoid landscape fragmentation, prioritize ecological protection, and improve the quality of habitats in the geographic location.
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