In recent years, research on multi-object behavior recognition methods based on pose estimation has made progress. However, in dense scenes, multi-object behavior recognition faces problems such as heavy occlusion, many small-scale objects, and ...

• The parallel branch structure for classification and location is proposed.
• The feature fusion mechanism improves the detectability of small objects.
• The dynamic weights generated by the object number optimize feature learning.

Shoeprint reconstruction is essential in forensic science, but it is also challenging due to various inconsistencies in the patterns, textures, sizes, abrasions, etc. of shoeprints. The computational reconstruction of sharper and more complete ...

• An end-to-end deep learning model focuses on shoeprint reconstruction for forensics.
• Reconstruction of existing patterns together with the generation of missing regions.
• Missing regions reconstruction is specifically designed based ...

Algorithmic paradigms such as divide-and-conquer (D&C) are proposed to guide developers in designing efficient algorithms, but it can still be difficult to apply algorithmic paradigms to practical tasks. To ease the usage of paradigms, many research ...

The large language models (LLMs) that everyone is using are not deployed locally. Users need to send relatively private and important data to LLM when using it. Handing over private and important data to LLM will cause people to worry, especially now ...

This paper introduces a portable, gamified exercise system with an embedded agent, specifically designed to aid the elderly in lower-body workouts using stationary bikes. The system integrates a custom-made Internet of Things (IoT) sensing unit, a ...

The inferior inner surface in the laser powder bed fusion process (LPBF) deteriorated mechanical performance of the final product and even has the potential to lead to process failure. This study proposed an online monitoring system with layer-...

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• Proposed layer-wise image-based online monitoring for laser powder bed fusion.
• Introduced a deep learning-based S d metric to evaluate the inner surface quality.
• Implemented an intelligent proportional controller for layer-wise ...

Three-way decision model is an effective way to deal with complex decision problems. However, since the three-way decision models now proposed are all based on a single decision criterion, the decision results typically reflect only one ...

• A new three-way decision model based on ensemble thinking is put forward.
• The core and candidate sets for a particular set are given based on set operations.
• The HCS, MCS and LCS are constructed by using K-means algorithm.
• A ...

Due to their quantitative nature, probabilistic programs pose non-trivial challenges for designing compositional and efficient program analyses. Many analyses for probabilistic programs rely on iterative approximation. This article presents an ...

In this paper, we study the problem of PAC learning halfspaces in the non-interactive local differential privacy model (NLDP). To breach the barrier of exponential sample complexity, previous results studied a relaxed setting where the server has ...

The shuffle model of differential privacy provides promising privacy-utility balances in decentralized, privacy-preserving data analysis. However, the current analyses of privacy amplification via shuffling lack both tightness and generality. To address ...

Referring Expression Comprehension (REC) is a task that involves grounding a specific object in an image based on a given referring query in the form of bounding boxes. Existing fully-supervised or weakly-supervised REC methods rely on either ...

• Recognize the rich semantics contained in images.
• Construct pseudo region-query pairs as training data.
• Present a fine-grained multi-modality fusion decoder for REC.

Distinct from the realm of perceived emotion research, induced emotion pertains to the emotional responses engendered within content consumers. This facet has garnered considerable attention and finds extensive application in the analysis of ...

Heterogeneous data is endemic due to the use of diverse models and settings of devices by hospitals in the field of medical imaging. However, there are few open-source frameworks for federated heterogeneous medical image analysis with ...

• A robust and generalizable privacy-preserving personalized federal learning method for heterogeneous medical image analysis.
• A novel decentralized cyclic secure aggregation mechanism with homomorphic encryption.
• PPPML-HMI has ...

With the development of society, the industrial structure of China's electric power industry is constantly optimized and upgraded. in order to achieve the goal of "carbon peak, carbon neutralization", there is an urgent need to solve the problem of ...

Cyber-Physical Systems (CPS) has emerged as a paradigm that connects cyber and physical worlds, which provides unprecedented opportunities to realize intelligent applications such as smart home, smart cities, and smart manufacturing. However, CPS faces a ...

In this paper, we study the Differentially Private Empirical Risk Minimization (DP-ERM) problem, considering both convex and non-convex loss functions. For cases where DP-ERM involves smooth (strongly) convex loss functions with or without non-...

We study federated unlearning, a novel problem to eliminate the impact of specific clients or data points on the global model learned via federated learning (FL). This problem is driven by the right to be forgotten and the privacy challenges in FL. We ...

Juxta-papillary duodenal diverticula (JPDD) are common but are usually asymptomatic, and they are often diagnosed by coincidence.

To analyse the anatomy and classification of JPDD and its relationship with biliary and ...

Video captioning aims to briefly describe the content of a video in accurate and fluent natural language, which is a hot research topic in multimedia processing. As a bridge between video and natural language, video captioning is a challenging ...

• A video captioning framework called global semantic enhancement network is proposed.
• It highlights features of informative frames in aggregated video representations.
• It enhances semantic correlations between video and language ...

Identifying the root cause of a software bug and fixing it is challenging. One reason for this is that many bugs are not reproducible during bug fixing.

We aim to provide an overview of existing works on bug reproduction and ...

• Systematic mapping of 134 primary studies.
• Bug localization and reproduction are mostly studied for Java and C programs.
• Most approaches were tested in experimental settings rather than active projects.