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- surveyAugust 2024JUST ACCEPTED
How to Improve Video Analytics with Action Recognition: A Survey
Action recognition refers to the process of categorizing a video by identifying and classifying the specific actions it encompasses. Videos originate from several domains, and within each domain of video analysis, comprehending actions holds paramount ...
- surveyAugust 2024JUST ACCEPTED
COVID-19 Modeling: A Review
The SARS-CoV-2 viruses and their triggered COVID-19 pandemic have fundamentally reshaped the world in almost every aspect, their evolution and influences remain. While over a million of literature have been produced on these unprecedented, overwhelming ...
- surveyJuly 2024JUST ACCEPTED
Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures
- Thanh Toan Nguyen,
- Nguyen Quoc Viet Hung,
- Thanh Tam Nguyen,
- Thanh Trung Huynh,
- Thanh Thi Nguyen,
- Matthias Weidlich,
- Hongzhi Yin
Recommender systems have become an integral part of online services due to their ability to help users locate specific information in a sea of data. However, existing studies show that some recommender systems are vulnerable to poisoning attacks ...
- surveyJuly 2024
Recent Advances for Aerial Object Detection: A Survey
ACM Computing Surveys (CSUR), Volume 56, Issue 12Article No.: 296, Pages 1–36https://doi.org/10.1145/3664598Aerial object detection, as object detection in aerial images captured from an overhead perspective, has been widely applied in urban management, industrial inspection, and other aspects. However, the performance of existing aerial object detection ...
- surveyJuly 2024
Multi-Task Learning in Natural Language Processing: An Overview
ACM Computing Surveys (CSUR), Volume 56, Issue 12Article No.: 295, Pages 1–32https://doi.org/10.1145/3663363Deep learning approaches have achieved great success in the field of Natural Language Processing (NLP). However, directly training deep neural models often suffer from overfitting and data scarcity problems that are pervasive in NLP tasks. In recent years,...
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- surveyJuly 2024
Meta-learning Approaches for Few-Shot Learning: A Survey of Recent Advances
ACM Computing Surveys (CSUR), Volume 56, Issue 12Article No.: 294, Pages 1–41https://doi.org/10.1145/3659943Despite its astounding success in learning deeper multi-dimensional data, the performance of deep learning declines on new unseen tasks mainly due to its focus on same-distribution prediction. Moreover, deep learning is notorious for poor generalization ...
- surveyJuly 2024
Visual Tuning
- Bruce X.B. Yu,
- Jianlong Chang,
- Haixin Wang,
- Lingbo Liu,
- Shijie Wang,
- Zhiyu Wang,
- Junfan Lin,
- Lingxi Xie,
- Haojie Li,
- Zhouchen Lin,
- Qi Tian,
- Chang Wen Chen
ACM Computing Surveys (CSUR), Volume 56, Issue 12Article No.: 297, Pages 1–38https://doi.org/10.1145/3657632Fine-tuning visual models has been widely shown promising performance on many downstream visual tasks. With the surprising development of pre-trained visual foundation models, visual tuning jumped out of the standard modus operandi that fine-tunes the ...
- surveyJuly 2024JUST ACCEPTED
Video Unsupervised Domain Adaptation with Deep Learning: A Comprehensive Survey
Video analysis tasks such as action recognition have received increasing research interest with growing applications in fields such as smart healthcare, thanks to the introduction of large-scale datasets and deep learning-based representations. However, ...
- surveyJuly 2024
A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers
ACM Computing Surveys (CSUR), Volume 56, Issue 11Article No.: 293, Pages 1–39https://doi.org/10.1145/3674501Relation extraction (RE) involves identifying the relations between entities from underlying content. RE serves as the foundation for many natural language processing (NLP) and information retrieval applications, such as knowledge graph completion and ...
- surveyJuly 2024
Object-centric Learning with Capsule Networks: A Survey
ACM Computing Surveys (CSUR), Volume 56, Issue 11Article No.: 291, Pages 1–291https://doi.org/10.1145/3674500Capsule networks emerged as a promising alternative to convolutional neural networks for learning object-centric representations. The idea is to explicitly model part-whole hierarchies by using groups of neurons called capsules to encode visual entities, ...
- surveyJuly 2024JUST ACCEPTED
A Survey on Federated Unlearning: Challenges, Methods, and Future Directions
In recent years, the notion of “the right to be forgotten” (RTBF) has become a crucial aspect of data privacy for digital trust and AI safety, requiring the provision of mechanisms that support the removal of personal data of individuals upon their ...
- surveyJuly 2024JUST ACCEPTED
A review and benchmark of feature importance methods for neural networks
Feature attribution methods (AMs) are a simple means to provide explanations for the predictions of black-box models like neural networks. Due to their conceptual differences, the numerous different methods, however, yield ambiguous explanations. While ...
- surveyJuly 2024JUST ACCEPTED
Deep Learning-based Depth Estimation Methods from Monocular Image and Videos: A Comprehensive Survey
Estimating depth from single RGB images and videos is of widespread interest due to its applications in many areas, including autonomous driving, 3D reconstruction, digital entertainment, and robotics. More than 500 deep learning-based papers have been ...
- surveyJuly 2024JUST ACCEPTED
A Comprehensive Analysis of Explainable AI for Malware Hunting
In the past decade, the number of malware variants has increased rapidly. Many researchers have proposed to detect malware using intelligent techniques, such as Machine Learning (ML) and Deep Learning (DL), which have high accuracy and precision. These ...
- surveyJuly 2024
AI-Based Affective Music Generation Systems: A Review of Methods and Challenges
ACM Computing Surveys (CSUR), Volume 56, Issue 11Article No.: 287, Pages 1–34https://doi.org/10.1145/3672554Music is a powerful medium for altering the emotional state of the listener. In recent years, with significant advancements in computing capabilities, artificial intelligence-based (AI-based) approaches have become popular for creating affective music ...
- surveyJuly 2024
Secure UAV (Drone) and the Great Promise of AI
ACM Computing Surveys (CSUR), Volume 56, Issue 11Article No.: 286, Pages 1–37https://doi.org/10.1145/3673225UAVs have found their applications in numerous applications from recreational activities to business in addition to military and strategic fields. However, research on UAVs is not going on as quickly as the technology. Especially, when it comes to the ...
- surveyJuly 2024
Macro Ethics Principles for Responsible AI Systems: Taxonomy and Directions
ACM Computing Surveys (CSUR), Volume 56, Issue 11Article No.: 289, Pages 1–37https://doi.org/10.1145/3672394Responsible AI must be able to make or support decisions that consider human values and can be justified by human morals. Accommodating values and morals in responsible decision making is supported by adopting a perspective of macro ethics, which views ...
- surveyJuly 2024
Research Progress of EEG-Based Emotion Recognition: A Survey
ACM Computing Surveys (CSUR), Volume 56, Issue 11Article No.: 288, Pages 1–49https://doi.org/10.1145/3666002Emotion recognition based on electroencephalography (EEG) signals has emerged as a prominent research field, facilitating objective evaluation of diseases like depression and motion detection for heathy people. Starting from the basic concepts of temporal-...
- surveyJune 2024
Lexical Semantic Change through Large Language Models: a Survey
ACM Computing Surveys (CSUR), Volume 56, Issue 11Article No.: 282, Pages 1–38https://doi.org/10.1145/3672393Lexical Semantic Change (LSC) is the task of identifying, interpreting, and assessing the possible change over time in the meanings of a target word. Traditionally, LSC has been addressed by linguists and social scientists through manual and time-...
- surveyJune 2024
Machine Learning with Confidential Computing: A Systematization of Knowledge
ACM Computing Surveys (CSUR), Volume 56, Issue 11Article No.: 281, Pages 1–40https://doi.org/10.1145/3670007Privacy and security challenges in Machine Learning (ML) have become increasingly severe, along with ML’s pervasive development and the recent demonstration of large attack surfaces. As a mature system-oriented approach, Confidential Computing has been ...