Diffusion models, a powerful and universal generative artificial intelligence technology, have achieved tremendous success and opened up new possibilities in diverse applications. In these applications, diffusion mode...
详细信息
Diffusion models, a powerful and universal generative artificial intelligence technology, have achieved tremendous success and opened up new possibilities in diverse applications. In these applications, diffusion models provide flexible high-dimensional data modeling, and act as a sampler for generating new samples under active control towards task-desired properties. Despite the significant empirical success, theoretical underpinnings of diffusion models are very limited, potentially slowing down principled methodological innovations for further harnessing and improving diffusion models. In this paper, we review emerging applications of diffusion models to highlight their sample generation capabilities under various control goals. At the same time, we dive into the unique working flow of diffusion models through the lens of stochastic processes. We identify theoretical challenges in analyzing diffusion models, owing to their complicated training procedure and interaction with the underlying data distribution. To address these challenges, we overview several promising advances, demonstrating diffusion models as an efficient distribution learner and a sampler. Furthermore, we introduce a new avenue in high-dimensional structured optimization through diffusion models, where searching for solutions is reformulated as a conditional sampling problem and solved by diffusion models. Lastly, we discuss future directions about diffusion models. The purpose of this paper is to provide a well-rounded exposure for stimulating forward-looking theories and methods of diffusion models.
Total shoulder arthroplasty is a standard restorative procedure practiced by orthopedists to diagnose shoulder arthritis in which a prosthesis replaces the whole joint or a part of the *** is often challenging for doc...
详细信息
Total shoulder arthroplasty is a standard restorative procedure practiced by orthopedists to diagnose shoulder arthritis in which a prosthesis replaces the whole joint or a part of the *** is often challenging for doctors to identify the exact model and manufacturer of the prosthesis when it is *** paper proposes a transfer learning-based class imbalance-aware prosthesis detection method to detect the implant’s manufacturer automatically from shoulder X-ray *** framework of the method proposes a novel training approach and a new set of batch-normalization,dropout,and fully convolutional layers in the head *** employs cyclical learning rates and weighting-based loss calculation *** modifications aid in faster convergence,avoid local-minima stagnation,and remove the training bias caused by imbalanced *** proposed method is evaluated using seven well-known pre-trained models of VGGNet,ResNet,and DenseNet *** is performed on a shoulder implant benchmark dataset consisting of 597 shoulder X-ray *** proposed method improves the classification performance of all pre-trained models by 10–12%.The DenseNet-201-based variant has achieved the highest classification accuracy of 89.5%,which is 10%higher than existing ***,to validate and generalize the proposed method,the existing baseline dataset is supplemented to six classes,including samples of two more implant *** results have shown average accuracy of 86.7%for the extended dataset and show the preeminence of the proposed method.
The Internet of Things (IoT) and edge-assisted networking infrastructures are capable of bringing data processing and accessibility services locally at the respective edge rather than at a centralized module. These in...
详细信息
The Internet of Things (IoT) and edge-assisted networking infrastructures are capable of bringing data processing and accessibility services locally at the respective edge rather than at a centralized module. These infrastructures are very effective in providing a fast response to the respective queries of the requesting modules, but their distributed nature has introduced other problems such as security and privacy. To address these problems, various security-assisted communication mechanisms have been developed to safeguard every active module, i.e., devices and edges, from every possible vulnerability in the IoT. However, these methodologies have neglected one of the critical issues, which is the prediction of fraudulent devices, i.e., adversaries, preferably as early as possible in the IoT. In this paper, a hybrid communication mechanism is presented where the Hidden Markov Model (HMM) predicts the legitimacy of the requesting device (both source and destination), and the Advanced Encryption Standard (AES) safeguards the reliability of the transmitted data over a shared communication medium, preferably through a secret shared key, i.e., , and timestamp information. A device becomes trusted if it has passed both evaluation levels, i.e., HMM and message decryption, within a stipulated time interval. The proposed hybrid, along with existing state-of-the-art approaches, has been simulated in the realistic environment of the IoT to verify the security measures. These evaluations were carried out in the presence of intruders capable of launching various attacks simultaneously, such as man-in-the-middle, device impersonations, and masquerading attacks. Moreover, the proposed approach has been proven to be more effective than existing state-of-the-art approaches due to its exceptional performance in communication, processing, and storage overheads, i.e., 13%, 19%, and 16%, respectively. Finally, the proposed hybrid approach is pruned against well-known security attacks
We propose a first-order sampling method called the Metropolis-adjusted Preconditioned Langevin Algorithm for approximate sampling from a target distribution whose support is a proper convex subset of Rd. Our proposed...
详细信息
Dirac-vortex microcavity laser based on InAs/InGaAs quantum dots have been experimentally realized on silicon *** topological laser features a large spectral range and high robustness against variations such as cavity...
详细信息
Dirac-vortex microcavity laser based on InAs/InGaAs quantum dots have been experimentally realized on silicon *** topological laser features a large spectral range and high robustness against variations such as cavity size.
Handwriting is a unique and significant human feature that distinguishes them from one *** are many researchers have endeavored to develop writing recognition systems utilizing specific signatures or symbols for perso...
详细信息
Handwriting is a unique and significant human feature that distinguishes them from one *** are many researchers have endeavored to develop writing recognition systems utilizing specific signatures or symbols for person identification through ***,such systems are susceptible to forgery,posing security *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** innovative method is intricately designed,encompassing five distinct phases:data collection,preprocessing,feature extraction,significant feature selection,and *** key advancement lies in the creation of a novel dataset specifically tailored for Bengali handwriting(BHW),setting the foundation for our comprehensive ***-preprocessing,we embarked on an exhaustive feature extraction process,encompassing integration with kinematic,statistical,spatial,and composite *** meticulous amalgamation resulted in a robust set of 91 *** enhance the efficiency of our system,we employed an analysis of variance(ANOVA)F test and mutual information scores approach,meticulously selecting the most pertinent *** the identification phase,we harnessed the power of cutting-edge deep learning models,notably the Convolutional Neural Network(CNN)and Bidirectional Long Short-Term Memory(BiLSTM).These models underwent rigorous training and testing to accurately discern individuals based on their handwriting ***,our methodology introduces a groundbreaking hybrid model that synergizes CNN and BiLSTM,capitalizing on fine motor features for enhanced individual ***,our experimental results unde
With the exponential growth in information related applications and the continuous increase in voice over IP (VoIP) applications, the carriers are expanding their networks to provide improved services to their end use...
详细信息
Edge computing devices in Internet-of-Things (IoT) systems are being widely used in diverse application domains including industrial automation, surveillance, and smart housing. These applications typically employ a l...
详细信息
In the era of network communication,digital image encryption(DIE)technology is critical to ensure the security of image ***,there has been limited research on combining deep learning neural networks with chaotic mappi...
详细信息
In the era of network communication,digital image encryption(DIE)technology is critical to ensure the security of image ***,there has been limited research on combining deep learning neural networks with chaotic mapping for the encryption of digital ***,this paper addresses this gap by studying the generation of pseudo-random sequences(PRS)chaotic signals using dual logistic chaotic *** signals are then predicted using long and short-term memory(LSTM)networks,resulting in the reconstruction of a new chaotic *** the research process,it was discovered that there are numerous training parameters associated with the LSTM network,which can hinder training *** overcome this challenge and improve training efficiency,the paper proposes an improved particle swarm optimization(IPSO)algorithm to optimize the LSTM ***,the obtained chaotic signal from the optimized model training is further scrambled,obfuscated,and diffused to achieve the final encrypted *** research presents a digital image encryption(DIE)algorithm based on a double chaotic map(DCM)and *** algorithm demonstrates a high average NPCR(Number of Pixel Change Rate)of 99.56%and a UACI(Unified Average Changing Intensity)value of 33.46%,indicating a strong ability to resist differential ***,the proposed algorithm realizes secure and sensitive digital image encryption,ensuring the protection of personal information in the Internet environment.
Purpose: This study aims to investigate and compare three nonplanar (NP) slicing algorithms. The algorithms aim to control the layer thickness variation (LTV), which is a common issue in supportless fabrication of fre...
详细信息
暂无评论