In natural language processing, data acquisition and preprocessing techniques are significant for experiments involving training models on cleaned data. This paper describes the formation of a dataset of ugly and dero...
详细信息
This paper presents an area-efficient 0.8 V current-mode bandgap reference (BGR) in 22nm fully-depleted silicon-on-insulator (FD-SOI) CMOS process. Implementing the body bias technique allows for smaller device sizes ...
详细信息
Die bonding materials are critical in power module packaging, as their ability to withstand the high temperatures generated during device operation directly impacts performance and longevity in real-world applications...
详细信息
This paper studies the power density limits of propulsion motor for electric aircraft considering thermal aspects and breakdown voltage reduction of insulation. The study em-ploys multi-objective optimization (MOO) to...
详细信息
The rapid adoption of cloud storage for healthcare data brings enhanced accessibility and streamlined data management, but it also introduces significant security and privacy challenges. This paper presents a multi-la...
详细信息
Appearance-based dynamic Hand Gesture Recognition(HGR)remains a prominent area of research in Human-computer Interaction(HCI).Numerous environmental and computational constraints limit its real-time *** addition,the p...
详细信息
Appearance-based dynamic Hand Gesture Recognition(HGR)remains a prominent area of research in Human-computer Interaction(HCI).Numerous environmental and computational constraints limit its real-time *** addition,the performance of a model decreases as the subject’s distance from the camera *** study proposes a 3D separable Convolutional Neural Network(CNN),considering the model’s computa-tional complexity and recognition *** 20BN-Jester dataset was used to train the model for six gesture *** achieving the best offline recognition accuracy of 94.39%,the model was deployed in real-time while considering the subject’s attention,the instant of performing a gesture,and the subject’s distance from the *** being discussed in numerous research articles,the distance factor remains unresolved in real-time deployment,which leads to degraded recognition *** the proposed approach,the distance calculation substantially improves the classification performance by reducing the impact of the subject’s distance from the ***,the capability of feature extraction,degree of relevance,and statistical significance of the proposed model against other state-of-the-art models were validated using t-distributed Stochastic Neighbor Embedding(t-SNE),Mathew’s Correlation Coefficient(MCC),and the McNemar test,*** observed that the proposed model exhibits state-of-the-art outcomes and a comparatively high significance level.
Inverse Reinforcement Learning (IRL) and Reinforcement Learning from Human Feedback (RLHF) are pivotal methodologies in reward learning, which involve inferring and shaping the underlying reward function of sequential...
详细信息
Inverse Reinforcement Learning (IRL) and Reinforcement Learning from Human Feedback (RLHF) are pivotal methodologies in reward learning, which involve inferring and shaping the underlying reward function of sequential decision-making problems based on observed human demonstrations and feedback. Most prior work in reward learning has relied on prior knowledge or assumptions about decision or preference models, potentially leading to robustness issues. In response, this paper introduces a novel linear programming (LP) framework tailored for offline reward learning. Utilizing pre-collected trajectories without online exploration, this framework estimates a feasible reward set from the primal-dual optimality conditions of a suitably designed LP, and offers an optimality guarantee with provable sample efficiency. Our LP framework also enables aligning the reward functions with human feedback, such as pairwise trajectory comparison data, while maintaining computational tractability and sample efficiency. We demonstrate that our framework potentially achieves better performance compared to the conventional maximum likelihood estimation (MLE) approach through analytical examples and numerical experiments. Copyright 2024 by the author(s)
Internet of Things (IoT) defense against malicious activities heavily depends on intrusion detection systems (IDS). But unbalanced datasets and fast changing network conditions, prevalent in IoT applications, are comm...
详细信息
The measurement of soil water content plays a crucial role in the management of water resources, particularly in agriculture, which consumes over 80% of the managed water supply. An accurate and efficient model for me...
详细信息
Hydrogen fuel cells offer a clean and efficient energy source for various applications, including transportation. However, the nonlinear output voltage and current characteristics of fuel cells present challenges in t...
详细信息
暂无评论