Feature Fusion Vision Transformer for Fine-Grained Visual Categorization

The core for tackling the fine-grained visual categorization (FGVC) is to learn subtle yet discriminative features. Most previous works achieve this by explicitly selecting the discriminative parts or integrating the attention mechanism via CNN-based approaches.However, these methods enhance the computational complexity and make the modeldominated by the regions containing the most of the objects. Recently, vision trans-former (ViT) has achieved SOTA performance on general image recognition tasks. Theself-attention mechanism aggregates and weights the information from all patches to the classification token, making it perfectly suitable for FGVC. Nonetheless, the classifi-cation token in the deep layer pays more attention to the global information, lacking the local and low-level features that are essential for FGVC. In this work, we proposea novel pure transformer-based framework Feature Fusion Vision Transformer (FFVT)where we aggregate the important tokens from each transformer layer to compensate thelocal, low-level and middle-level information. We design a novel token selection mod-ule called mutual attention weight selection (MAWS) to guide the network effectively and efficiently towards selecting discriminative tokens without introducing extra param-eters. We verify the effectiveness of FFVT on three benchmarks where FFVT achieves the state-of-the-art performance.Comment: 9 pages, 2 figures, 3 table

Supreme People\u27s Court Annual Report on Intellectual Property Cases (2015) (China)

The Supreme People’s Court of China began publishing its Annual Report on Intellectual Property Cases in 2008. The annual reports, published in April each year, summarize and review new intellectual property cases. This translation includes all 32 cases and 38 legal issues of the 2015 Annual Report. It addresses various areas of law related to intellectual property, including patent law, trademark law, copyright law, unfair competition law, antitrust law, new plant product patent law, and laws related to procedural and evidentiary issues in intellectual property cases. While China is not a common law country, these cases serve as guidelines for lower courts in adjudicating intellectual property disputes

Supreme People\u27s Court Annual Report on Intellectual Property Cases (2015) (China)

The Supreme People’s Court of China began publishing its Annual Report on Intellectual Property Cases in 2008. The annual reports, published in April each year, summarize and review new intellectual property cases. This translation includes all 32 cases and 38 legal issues of the 2015 Annual Report. It addresses various areas of law related to intellectual property, including patent law, trademark law, copyright law, unfair competition law, antitrust law, new plant product patent law, and laws related to procedural and evidentiary issues in intellectual property cases. While China is not a common law country, these cases serve as guidelines for lower courts in adjudicating intellectual property disputes

A Generalized Calibrated Bayesian Hierarchical Modeling Approach to Basket Trials With Multiple Endpoints

A basket trial simultaneously evaluates a treatment in multiple cancer subtypes, offering an effective way to accelerate the drug development in multiple indications. Many basket trials are designed and monitored based on a single efficacy endpoint, primarily the tumor response. For molecular targeted or immunotherapy agents, however, a single efficacy endpoint cannot adequately characterize the treatment effect. It is increasingly important to use more complex endpoints to comprehensively assess the risk–benefit profile of such targeted therapies. We extend the calibrated Bayesian hierarchical modeling approach (Chu and Yuan, 2018a) to monitor phase II basket trials with multiple endpoints. We propose two generalizations, one based on the latent variable approach and the other based on the multinomial-normal hierarchical model, to accommodate different types of endpoints and dependence assumptions regarding information sharing. We introduce shrinkage parameters as functions of statistics measuring homogeneity among subgroups, and propose a general calibration approach to determine the functional forms. Theoretical properties of the generalized hierarchical models are investigated. Simulation studies demonstrate that the monitoring procedure based on the generalized approach yields desirable operating characteristics