Titlebook: Artificial Intelligence; Third CAAI Internati Lu Fang,Jian Pei,Ruiping Wang Conference proceedings 2024 The Editor(s) (if applicable) and T

Garfield

書目名稱Artificial Intelligence影響因子(影響力)




書目名稱Artificial Intelligence影響因子(影響力)學科排名




書目名稱Artificial Intelligence網(wǎng)絡公開度




書目名稱Artificial Intelligence網(wǎng)絡公開度學科排名




書目名稱Artificial Intelligence被引頻次




書目名稱Artificial Intelligence被引頻次學科排名




書目名稱Artificial Intelligence年度引用




書目名稱Artificial Intelligence年度引用學科排名




書目名稱Artificial Intelligence讀者反饋




書目名稱Artificial Intelligence讀者反饋學科排名

intention

Blind Adversarial Training: Towards Comprehensively Robust Models Against Blind Adversarial Attacksning. Most existing AT approaches can be grouped into restricted and unrestricted approaches. Restricted AT requires a prescribed uniform budget for AEs during training, with the obtained results showing high sensitivity to the budget. In contrast, unrestricted AT uses unconstrained AEs, and these o

咽下

TOAC: Try-On Aligning Conformer for?Image-Based Virtual Try-On Alignmentof portraits. Image-based virtual try-on generally consists of two steps: Image-based Virtual Try-on Alignment and Image-based Virtual Try-on Generation. In this paper, we focus on Image-based Virtual Try-on Alignment (IVTA), which plays a pivotal role in virtual try-on and aligns the target garment

專心

GIST: Transforming Overwhelming Information into Structured Knowledge with Large Language Models language models to analyze and organize the information, generating structured results, including summaries, key points, and questions and answers. The system also utilizes a multimodal information processing approach to enhance comprehension of the content. As the user’s knowledge base grows, GIST

GROG

AIGCIQA2023: A Large-Scale Image Quality Assessment Database for?AI Generated Images: From the?Perspniques, AI-based image generation has been applied to various fields. However, AI Generated Images (AIGIs) may have some unique distortions compared to natural images, thus many generated images are not qualified for real-world applications. Consequently, it is important and significant to study sub

共同給與

TST: Time-Sparse Transducer for?Automatic Speech Recognitiones a great memory footprint and computing time when processing a long decoding sequence. To solve this problem, we propose a model named time-sparse transducer, which introduces a time-sparse mechanism into transducer. In this mechanism, we obtain the intermediate representations by reducing the tim

jabber

Enhancing Daily Life Through an?Interactive Desktop Robotics Systemlarge language models and performing a variety of desktop-related tasks. The robot’s capabilities include organizing cluttered objects on tables, such as dining tables or office desks, placing them into storage cabinets, as well as retrieving specific items from drawers upon request. This paper prov

Foreknowledge

閃光你我

A Weakly Supervised Learning Method for Recognizing Childhood Tic Disordersy. In this work, we focus on weakly supervised learning methods for recognizing childhood tic disorders. In situations with limited data availability, we design a relative probability metric based on the characteristics of the data and a multi-phase learning algorithm is proposed based on relative p

裁決

Detecting Software Vulnerabilities Based on?Hierarchical Graph Attention Networkcation or regression models from the source code to detect vulnerabilities, which require lots of high-quality labeled vulnerabilities. However, high-quality labeled vulnerabilities are not easy to be obtained in practical applications. To alleviate this problem, we present an effective and unsuperv