Improving Model Drift for Robust Object Tracking

Discriminative correlation filters show excellent performance in object tracking. However, in complex scenes, the apparent characteristics of the tracked target are variable, which makes it easy to pollute the model and cause the model drift. In this paper, considering that the secondary peak has a greater impact on the model update, we propose a method for detecting the primary and secondary peaks of the response map. Secondly, a novel confidence function which uses the adaptive update discriminant mechanism is proposed, which yield good robustness. Thirdly, we propose a robust tracker with correlation filters, which uses hand-crafted features and can improve model drift in complex scenes. Finally, in order to cope with the current trackers' multi-feature response merge, we propose a simple exponential adaptive merge approach. Extensive experiments are performed on OTB2013, OTB100 and TC128 datasets. Our approach performs superiorly against several state-of-the-art trackers while runs at speed in real time.Comment: 7 pages, 6 figures, 4 table

Efficient refinements on YOLOv3 for real-time detection and assessment of diabetic foot Wagner grades

Currently, the screening of Wagner grades of diabetic feet (DF) still relies on professional podiatrists. However, in less-developed countries, podiatrists are scarce, which led to the majority of undiagnosed patients. In this study, we proposed the real-time detection and location method for Wagner grades of DF based on refinements on YOLOv3. We collected 2,688 data samples and implemented several methods, such as a visual coherent image mixup, label smoothing, and training scheduler revamping, based on the ablation study. The experimental results suggested that the refinements on YOLOv3 achieved an accuracy of 91.95% and the inference speed of a single picture reaches 31ms with the NVIDIA Tesla V100. To test the performance of the model on a smartphone, we deployed the refinements on YOLOv3 models on an Android 9 system smartphone. This work has the potential to lead to a paradigm shift for clinical treatment of the DF in the future, to provide an effective healthcare solution for DF tissue analysis and healing status.Comment: 11 pages with 11 figure

Transformations preserving properties and properties preserved by transformations in fair transition systems (extended abstract)

Chandy and Misra's Unity, Back's Action Systems and Lamport's Temporal Logic of Actions (TLA) are three prime examples of specification formalisms for concurrent systems viewed as fair transition systems. The first two examples, and to a lesser extent the latter, also advocate a design methodology for formal derivation of concurrent systems or, rather, concurrent algorithms. Their program can be summarized as positing that algorithms should be designed without specific program control being forced upon the designer and that algorithms should be specified using properties that are (easily shown to be) preserved by the various transformations that one might use during the derivation process. For Misra and Chandy such transformations include union (i.e., parallel composition) and some forms of refinement but not hiding of variables. Back does consider hiding but ignores union as a property preserving transformation; as does, e.g., Lamport in his TLA. The first aim of our research is to further this program and to find properties and a larger class of transformations (including all of the above mentioned) such that the properties are preserved by this class. A typical result is that the Unity unless property, that is known to be preserved by union and superposition, is also preserved by hiding and refinement (as we define them). Our second aim, prompted by the growth of the collection of transformations and novel to this approach, is to consider their interaction—e.g., a superposition should refine the underlying program. Our third, also novel, aim is to investigate how much ‘leeway’ there is in defining such properties and transformations. Here, one result is that the Unity invariance property, p iv in T, is the weakest property that implies that p is true everywhere on the computations of T and that is preserved by union. This abstract's results are summarized in Table 2 and should be contrasted with Table 1 which summarizes the relevant ‘state of the art’. We use temporal logic and a subset of it YAL as program notation. Our results, however, are in no way restricted to YAL and apply equally well to, e.g., TLA, Unity, Action Systems, Manna and Pnueli's transition systems or Lynch and Tuttle's I/O automata

Transformations preserving properties and properties preserved by transformations in fair transition systems (extended abstract)

Chandy and Misra's Unity, Back's Action Systems and Lamport's Temporal Logic of Actions (TLA) are three prime examples of specification formalisms for concurrent systems viewed as fair transition systems. The first two examples, and to a lesser extent the latter, also advocate a design methodology for formal derivation of concurrent systems or, rather, concurrent algorithms. Their program can be summarized as positing that algorithms should be designed without specific program control being forced upon the designer and that algorithms should be specified using properties that are (easily shown to be) preserved by the various transformations that one might use during the derivation process. For Misra and Chandy such transformations include union (i.e., parallel composition) and some forms of refinement but not hiding of variables. Back does consider hiding but ignores union as a property preserving transformation; as does, e.g., Lamport in his TLA. The first aim of our research is to further this program and to find properties and a larger class of transformations (including all of the above mentioned) such that the properties are preserved by this class. A typical result is that the Unity unless property, that is known to be preserved by union and superposition, is also preserved by hiding and refinement (as we define them). Our second aim, prompted by the growth of the collection of transformations and novel to this approach, is to consider their interaction—e.g., a superposition should refine the underlying program. Our third, also novel, aim is to investigate how much ‘leeway’ there is in defining such properties and transformations. Here, one result is that the Unity invariance property, p iv in T, is the weakest property that implies that p is true everywhere on the computations of T and that is preserved by union. This abstract's results are summarized in Table 2 and should be contrasted with Table 1 which summarizes the relevant ‘state of the art’. We use temporal logic and a subset of it YAL as program notation. Our results, however, are in no way restricted to YAL and apply equally well to, e.g., TLA, Unity, Action Systems, Manna and Pnueli's transition systems or Lynch and Tuttle's I/O automata

TRAL: A Tag-Aware Recommendation Algorithm Based on Attention Learning

A social tagging system improves recommendation performance by introducing tags as auxiliary information. These tags are text descriptions of target items provided by individual users, which can be arbitrary words or phrases, so they can provide more abundant information about user interests and item characteristics. However, there are many problems to be solved in tag information, such as data sparsity, ambiguity, and redundancy. In addition, it is difficult to capture multi-aspect user interests and item characteristics from these tags, which is essential to the recommendation performance. In the view of these situations, we propose a tag-aware recommendation model based on attention learning, which can capture diverse tag-based potential features for users and items. The proposed model adopts the embedding method to produce dense tag-based feature vectors for each user and each item. To compress these vectors into a fixed-length feature vector, we construct an attention pooling layer that can automatically allocate different weights to different features according to their importance. We concatenate the feature vectors of users and items as the input of a multi-layer fully connected network to learn non-linear high-level interaction features. In addition, a generalized linear model is also conducted to extract low-level interaction features. By integrating these features of different types, the proposed model can provide more accurate recommendations. We establish extensive experiments on two real-world datasets to validate the effect of the proposed model. Comparable results show that our model perform better than several state-of-the-art tag-aware recommendation methods in terms of HR and NDCG metrics. Further ablation studies also demonstrate the effectiveness of attention learning

A Novel Method to Rank Influential Nodes in Complex Networks Based on Tsallis Entropy

With the rapid development of social networks, it has become extremely important to evaluate the propagation capabilities of the nodes in a network. Related research has wide applications, such as in network monitoring and rumor control. However, the current research on the propagation ability of network nodes is mostly based on the analysis of the degree of nodes. The method is simple, but the effectiveness needs to be improved. Based on this problem, this paper proposes a method that is based on Tsallis entropy to detect the propagation ability of network nodes. This method comprehensively considers the relationship between a node’s Tsallis entropy and its neighbors, employs the Tsallis entropy method to construct the TsallisRank algorithm, and uses the SIR (Susceptible, Infectious, Recovered) model for verifying the correctness of the algorithm. The experimental results show that, in a real network, this method can effectively and accurately evaluate the propagation ability of network nodes

Effects of Hygrothermal and Salt Mist Ageing on the Properties of Epoxy Resins and Their Composites

Epoxy and epoxide composites have a wide range of outdoor applications wherein they are affected by ageing. In this study, epoxy casting plates and epoxy-based composite rods for use in overhead conductors were prepared. A concurrent investigation concerning the ageing of epoxy resins and their carbon fibre composites was carried out via artificially accelerated experiments under hygrothermal and salt mist conditions. The moisture penetration along the depth, water absorption, appearance, hardness, density of the epoxy resins, and variation patterns of the impact strength and tensile strength of the epoxy-based composites were investigated. The ageing mechanisms were explored using Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). Both ageing modes had essentially similar influences on the properties of the resins and their composites; moreover, they did not significantly affect the chemical structure and microstructure of the epoxy resin, with the physical adsorption of water primarily observed during the ageing process. The moisture absorption behaviour of the epoxy obeyed Fick’s law. Although the water penetration rate in the salt mist ageing mode was slightly higher than that in the hygrothermal ageing mode during the early ageing stage, it was essentially the same during the later stage. The final moisture absorption rate at saturation was approximately 1.1% under both modes. The flexural strengths and impact strengths of the composites in both ageing modes followed a similar trend. They decreased gradually with the ageing time and then stabilized at almost the same value. The flexural strength was reduced from 803 MPa to 760 MPa and the impact strength from 383 J/m2 to 310 J/m2, indicating a decrease of approximately 5.4% and 19%, respectively. The absorbed water during the ageing process caused micro-cracks at the interface between the fibres and resin, weakening the interfacial strength and reducing the mechanical properties of the composites