The transformer architecture has achieved remarkable success in medical image analysis owing to its powerful capability for capturing long-range dependencies. However, due to the lack of intrinsic inductive bias in mo...
详细信息
Colorectal cancer (CRC) is one of the prominent causes of cancer-related morbidity and mortality worldwide. More AI-assisted methods are conducted for early polyp detection and segmentation to improve the screening ef...
详细信息
ISBN:
(纸本)9798400718779
Colorectal cancer (CRC) is one of the prominent causes of cancer-related morbidity and mortality worldwide. More AI-assisted methods are conducted for early polyp detection and segmentation to improve the screening efficacy. However, previous solutions generally exhibit weak segmentation performance due to irregular structures of polyps, while the model robustness suffers from background noise of homogeneous neighbors. To this end, we propose a novel Multi-Focus Attention Network (MFANet) to encode multi-dimensional information (i.e., scale, contour, and shape) as fine-grained cues for polyp segmentation. Concretely, a Scale-Residual-Aware Attention (SRAA) is designed to apply the residual operation over each layer of the feature pyramid architecture, which could minimize the feature interference among different scales. To improve the model robustness, a Geometry-Structure-Aware Attention (GSAA) is formulated to integrate and refine multi-dimensional geometric features via a Channel-Wise Enhance Attention (CWEA), which condenses the spatial information and recalibrates the channel importance for adaptive feature recalibration. Experiments on six public datasets indicate the effectiveness of the proposed method. Notably, on the more challenging BKAI dataset, which is featured by tiny polyps with serious interference of homogeneous neighboring region, our MFANet can outperform the state-of-the-art (SOTA) methods. Additionally, it is experimentally verified that our approach consistently exhibits better segmentation performance with higher robustness against different attack strategies (i.e., FGSM, WaNet and PGD).
In real-world scenarios, scanned point clouds are often incomplete due to occlusion issues. The tasks of self-supervised and weakly-supervised point cloud completion involve reconstructing missing regions of these inc...
详细信息
Despite the significant achievements in the development of automation technologies, the application of autonomous robots to improve the production efficiency of small-scale indus-tries has been largely ignored. While ...
Despite the significant achievements in the development of automation technologies, the application of autonomous robots to improve the production efficiency of small-scale indus-tries has been largely ignored. While there has been excellent progress in industrial image processing systems implementation, most of the work has focused on a unique aspect of specific objects rather than introducing a general inspection system. Thus, this paper discusses the critical industrial topic of quality control, which develops rapidly through the use of autonomous systems. Given the high cost of implementing automated systems, this paper presents an affordable low-budget solution for the visual inspection system. This method of inspecting screw dimensions consists of four visual inspection parts and a special mechanical supporting structure. The designed system was able to check the overall screw dimensions, including screw head diameter, screw head driven type, screw length, screw thread length, and screw head thickness. It could also separate the qualified screws from the unqualified ones after the inspection process. The accuracy of most inspection cases is 100%, meaning the error ranges within 0.1mm, which meets all the non-negotiable requirements and most of the target requirements. The visual inspection parts can be further enhanced by building a template matching library that includes different angles of the screw head or by using Hough Transform to identify the defect types of the screw thread.
The dynamic expansion architecture is becoming popular in class incremental learning, mainly due to its advantages in alleviating catastrophic forgetting. However, task confusion is not well assessed within this frame...
详细信息
As LLM-as-a-Judge emerges as a new paradigm for assessing large language models (LLMs), concerns have been raised regarding the alignment, bias, and stability of LLM evaluators. While substantial work has focused on a...
详细信息
In this paper, we propose a simplified cubic polynomial R-D model with corresponding rate control methods for Versatile Video Coding (VVC) intra frame coding. First, we explore the rate-distortion (R-D) characteristic...
In this paper, we propose a simplified cubic polynomial R-D model with corresponding rate control methods for Versatile Video Coding (VVC) intra frame coding. First, we explore the rate-distortion (R-D) characteristics of VVC intra coding. By comparing several potential R-D modeling approaches, a new intra coding R-D model has been proposed based on the simplified cubic polynomial function. Subsequently, we derive the corresponding $R-\lambda$ model and introduce a complexity measurement to improve the performance of intra frame rate control. Furthermore, we propose a Coding Tree Unit (CTU)-level rate control method based on the newly proposed R-D model and further develop a pre-compression-based approach on this basis. Experimental results show that the proposed method can achieve 1.87% and 0.55% bit rate reduction for All-Intra (AI) and Random-Access (RA) configurations over the original rate control in VVC Test Model (VTM), while the computational complexity increment is negligible. Meanwhile, the enhanced bit rate accuracy from rate control has been observed in the proposed methods.
Desires motivate humans to interact autonomously with the complex world. In contrast, current AI agents require explicit task specifications, such as instructions or reward functions, which constrain their autonomy an...
详细信息
Anomaly detection and localization are widely used in industrial manufacturing for its efficiency and effectiveness. Anomalies are rare and hard to collect and supervised models easily over-fit to these seen anomalies...
详细信息
Due to the proliferation of internet evaluations brought on by the rising demand for smartphones, consumers find it challenging to make accurate selections when purchasing. In this paper, we offer ensemble voting meth...
详细信息
暂无评论