In our previous work, i.e., HNF-Net, high-resolution feature representation and light-weight non-local self-attention mechanism are exploited for brain tumor segmentation using multi-modal MR imaging. In this paper, w...
详细信息
Recording the provenance of scientific computation results is key to the support of traceability, reproducibility and quality assessment of data products. Several data models have been explored to address this need, p...
详细信息
Waste cooking oil (WCO) represents one of the most available renewable energy sources to produce solid alcohol biofuel (SABF) and biodiesel. The objective of this work is to conduct energy and cost balances for biodie...
详细信息
Existing text classification algorithms generally have limitations in terms of text length and yield poor classification results for long texts. To address this problem, we propose a BERT-based long text classificatio...
详细信息
Bladder cancer (BC) remains a significant global health challenge, requiring the development of accurate predictive models for diagnosis. In this study, a new Binary Modified White Whale Optimization (B-MBWO) algorith...
详细信息
This perspective piece is the result of a Generative Adversarial Collaboration (GAC) tackling the question 'How does neural activity represent probability distributions?'. We have addressed three major obstacl...
详细信息
— Robotic grasping in the open world is a critical component of manufacturing and automation processes. While numerous existing approaches depend on 2D segmentation output to facilitate the grasping procedure, accura...
详细信息
Movable antenna (MA) has been recognized as a promising technology to enhance the performance of wireless communication and sensing by enabling antenna movement. Such a significant paradigm shift from conventional fix...
详细信息
Movable antenna (MA) has been recognized as a promising technology to enhance the performance of wireless communication and sensing by enabling antenna movement. Such a significant paradigm shift from conventional fixed antennas (FAs) to MAs offers tremendous new opportunities towards realizing more versatile, adaptive and efficient next-generation wireless networks such as 6G. In this paper, we provide a comprehensive tutorial on the fundamentals and advancements in the area of MA-empowered wireless networks. First, we overview the historical development and contemporary applications of MA technologies. Next, to characterize the continuous variation in wireless channels with respect to antenna position and/or orientation, we present new field-response channel models tailored for MAs, which are applicable to narrowband and wideband systems as well as far-field and near-field propagation conditions. Subsequently, we review the state-of-the-art architectures for implementing MAs and discuss their practical constraints. A general optimization framework is then formulated to fully exploit the spatial degrees of freedom (DoFs) in antenna movement for performance enhancement in wireless systems. In particular, we delve into two major design issues for MA systems. First, we address the intricate antenna movement optimization problem for various communication and/or sensing systems to maximize the performance gains achievable by MAs. Second, we deal with the challenging channel acquisition issue in MA systems for reconstructing the channel mapping between arbitrary antenna positions inside the transmitter and receiver regions. Moreover, we show existing prototypes developed for MA-aided communication/sensing and the experimental results based on them. Finally, the extension of MA design to other wireless systems and its synergy with other emerging wireless technologies are discussed. We also highlight promising research directions in this area to inspire future investigatio
Predicting the distributions of path flow between origin-destination (OD) pairs in an urban road network is crucial for developing efficient traffic control and management strategies. Here, we use the large-scale taxi...
详细信息
In standard hospital blood tests, the traditional process requires doctors to manually isolate leukocytes from microscopic images of patients’ blood using microscopes. These isolated leukocytes are then categorized v...
详细信息
In standard hospital blood tests, the traditional process requires doctors to manually isolate leukocytes from microscopic images of patients’ blood using microscopes. These isolated leukocytes are then categorized via automatic leukocyte classifiers to determine the proportion and volume of different types of leukocytes present in the blood samples, aiding disease diagnosis. This methodology is not only time-consuming and labor-intensive, but it also has a high propensity for errors due to factors such as image quality and environmental conditions, which could potentially lead to incorrect subsequent classifications and misdiagnosis. Contemporary leukocyte detection methods exhibit limitations in dealing with images with fewer leukocyte features and the disparity in scale among different leukocytes, leading to unsatisfactory results in most instances. To address these issues, this paper proposes an innovative method of leukocyte detection: the Multi-level Feature Fusion and Deformable Self-attention DETR (MFDS-DETR). To tackle the issue of leukocyte scale disparity, we designed the High-level Screening-feature Fusion Pyramid (HS-FPN), enabling multi-level fusion. This model uses high-level features as weights to filter low-level feature information via a channel attention module and then merges the screened information with the high-level features, thus enhancing the model’s feature expression capability. Further, we address the issue of leukocyte feature scarcity by incorporating a multi-scale deformable self-attention module in the encoder and using the self-attention and cross-deformable attention mechanisms in the decoder, which aids in the extraction of the global features of the leukocyte feature maps. The effectiveness, superiority, and generalizability of the proposed MFDS-DETR method are confirmed through comparisons with other cutting-edge leukocyte detection models using the private WBCDD, public LISC and BCCD datasets. Our source code and private WBCCD
暂无评论