检索结果-内蒙古大学图书馆

IEEE Networking Letters 2025年第1期7卷 56-60页

作者： Mishra, Shruti Aggarwal, Virat Pal, Sujata Agarwal, Vidushi Indian Institute of Technology Ropar Department of Computer Science and Engineering Rupnagar140001 India

Payment channels support off-chain transactions by enhancing transaction speed and reducing fees in the main blockchain. However, the costs and complexity of the network increase as we increase the size of the network. To address these challenges, we propose Heuristic-Based Routing with Scheduling (HeRo) combining heuristic-based routing and scheduling techniques in Payment Channel Networks (PCNs). HeRo achieves a cost reduction of 32.71% and 73.08% compared with multi-charge PCN (MPCN-RP) and Dijkstra algorithms, respectively. © 2019 IEEE.

关键词： Network routing

来源：评论

学校读者我要写书评

暂无评论

Designing New Blood-Brain Barrier Penetrating Molecules Using Novel Hybridized Gravitational Search Algorithm and Explainable AI

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2127-2138页

作者： Singh, Vishakha Sharma, Ritesh Singh, Sanjay Kumar Indian Institute of Technology BHU Department of Computer Science and Engineering Varanasi221005 India

Artificial intelligence (AI) has emerged as a powerful tool in computational biology, where it is being used to analyze large datasets to detect difficult biological patterns. This has enabled the design of new drug molecules. In this article, a novel method called hybridized gravitational search algorithm (HyGSA) has been proposed to design novel blood-brain barrier penetrating peptides (B3P2s) with desirable characteristics that enable them to cross the blood-brain barrier (BBB) and deliver neurological drugs directly to the brain. The HyGSA has two important modules in the form of an explainable machine learning classifier (with an accuracy, f1-score, and area under the ROC curve (AUROC) of 84%, 84%, and 91%, respectively) and an explainable deep learning-based B3P2 classifier (with an accuracy, f1-score, and AUROC of 89%, 91%, and 95%, respectively). The former was used to determine the crucial hand-engineered features, and the latter was designed to determine the critical amino acids that play an important role in the BBB penetrability of a peptide. Moreover, the population of particles was sampled at the beginning of each iteration to ensure a good mix of particles with low, average, and high fitness. This was achieved using a novel method that takes inspiration from the subset-sum problem and uses the mean and variance of the distribution of particles. For the pilot study, some B3P2s were discovered and optimized from a set of cell-penetrating peptides. Lastly, a free online tool has been deployed at https://*** to help the scientific community discover and optimize B3P2s in protein sequences. © 2023 IEEE.

关键词： Peptides

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Dual Watermarking for Image Copyright Protection and Authentication

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6134-6145页

作者： Padhi, Sudev Kumar Tiwari, Archana Ali, Sk. Subidh Indian Institute of Technology Bhilai Department of Computer Science and Engineering Durg491002 India

Advancements in digital technologies make it easy to modify the content of digital images. Hence, ensuring digital images' integrity and authenticity is necessary to protect them against various attacks that manipulate them. We present a deep learning (DL) based dual invisible watermarking technique for performing source authentication, content authentication, and protecting digital content copyright of images sent over the internet. Beyond securing images, the proposed technique demonstrates robustness to content-preserving image manipulation attacks. It is also impossible to imitate or overwrite watermarks because the cryptographic hash of the image and the dominant features of the image in the form of perceptual hash are used as watermarks. We highlighted the need for source authentication to safeguard image integrity and authenticity, along with identifying similar content for copyright protection. After exhaustive testing, our technique obtained a high peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM), which implies there is a minute change in the original image after embedding our watermarks. Our trained model achieves high watermark extraction accuracy and satisfies two different objectives of verification and authentication on the same watermarked image. © 2020 IEEE.

关键词： Watermarking Copyright Protection Authentication Robustness Decoding Deep Learning Artificial Intelligence Accuracy PSNR Feature Extraction Copyright Protection Cryptographic Hash Deep Learning Image Authentication Perceptual Hash Watermarking

来源：评论

学校读者我要写书评

暂无评论

"Survey and analysis of blockchain technologies with respect to: properties, algorithms, architecture, models, evolution and framework"

引用

Multimedia Tools and Applications 2025年第14期84卷 13571-13615页

作者： Tiwari, Nikita Ranjan, Prakash Biswal, Pradeep Kumar Barde, Chetan Sinha, Neha Department of Computer Science and Engineering Indian Institute of Information Technology Bhagalpur Bhagalpur India Department of Electronics and Communication Engineering Indian Institute of Information Technology Bhagalpur Bhagalpur India

The growing realm of blockchain technology has captivated researchers and practitioners alike with its promise of decentralized, secure, and transparent transactions. This paper presents a comprehensive survey and analysis of various blockchain technologies, focusing on their fundamental properties, architectural designs, operational models, evolutionary trends, and overarching frameworks. Through an extensive review of existing literature and empirical studies, this research synthesizes the multifaceted landscape of blockchain, elucidating key concepts such as consensus mechanisms, smart contracts, scalability, interoperability, and privacy protocols. By examining the evolution of blockchain from its inception to its current state and beyond, this paper delineates the trajectory of technological advancements and identifies emerging paradigms. Furthermore, it critically evaluates the strengths and limitations of diverse blockchain architectures and models, offering insights into their applicability across different domains and use cases. Finally, this study culminates in the proposal of a comprehensive framework that encapsulates the essential elements necessary for understanding, implementing, and harnessing the transformative potential of blockchain technologies. Through this holistic analysis, this research contributes to a deeper understanding of blockchain ecosystems and provides valuable guidance for future research directions and practical implementations. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Utilizing attention mechanism with exemplar memory for improving domain adaptive person re-identification

引用

Multimedia Tools and Applications 2025年第16期84卷 16809-16834页

作者： Bhunia, Sugam Kr. Bakshi, Sambit Mukherjee, Imon Computer Science and Engineering Indian Institute of Information Technology Kalyani West Bengal Kalyani741235 India Computer Science and Engineering National Institute of Technology Rourkela Odisha Rourkela769008 India

In an Unsupervised Domain Adaptation (UDA) task, extracted features from the entire image lead to a negative transfer of irrelevant knowledge. An attention mechanism may highlight the suitable transferable region of an image. Here in this paper, the representative power of the deep re-identification (re-ID) network of an exemplar memory-based domain adaptive unsupervised Person Re-identification (PRId) model is increased with our chosen optimal Bottleneck Attention Module (BAM). Performance enhancement of the deep re-ID network itself has been attempted by very few research works, suffering from a misinterpretation of global features or non-determination of local features due to the presence of occlusions, background interference, view-point variations, low camera resolution, etc. The proposed approach shows remarkable performance improvement in these specific challenging scenarios. Our attention-enabled unsupervised PRId model is evaluated in a cross-platform environment by labeled training in the DukeMTMC-reID dataset and unlabeled target testing in the Market-1501 dataset. The proposed method also enhances the overall performance of our baseline architecture. It provides a 2.12% relative increment in mean Average Precision (mAP) value, 0.93% increment in Top-1 value, 0.33% increment in Top-10 value, and 0.53% increment in Top-20 value respectively. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Statistical tests

来源：评论

学校读者我要写书评

暂无评论

Reconstruction probability-based anomaly detection using variational auto-encoders

引用

International Journal of computers and Applications 2023年第3期45卷 231-237页

作者： Iqbal, Touseef Qureshi, Shaima Department of Computer Science and Engineering National Institute of Technology Jammu and Kashmir Srinagar India

Anomaly detection is a method of categorizing unexpected data points or events in a dataset. Variational Auto-Encoders (VAEs) have proved to handle complex problems in a variety of disciplines. We propose a technique for detecting anomalies based on the reconstruction probability of VAEs. The proposed method trains VAEs on three different datasets. The reconstruction probability is a much more principled and realistic anomaly score than the reconstruction error utilized by auto-encoders and other data compression methods because of the theoretical background and by including the concept of variability. The paper describes recent deep learning models for anomaly detection, as well as a comparison to other methodologies. Variational auto-encoders are trained on three different datasets, in an unsupervised setup to classify the anomalies, based on reconstruction probability. Further, the in-depth study of anomaly detection techniques is presented in this paper. The data are reconstructed using the VAEs generative characteristics to investigate the root cause of the anomalies. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Online Convex Optimization with Switching Cost and Delayed Gradients

引用

Performance Evaluation Review 2024年第4期51卷 22-23页

作者： Senapati, Spandan Vaze, Rahul Department of Computer Science & Engineering Indian Institute of Technology Kanpur India School of Technology and Computer Science Tata Institute of Fundamental Research India

We consider the online convex optimization (OCO) problem with quadratic and linear switching cost when at time t only gradient information for functions fτ, τ 16(Lµ+5) for the quadratic switching cost, and also show the bound to be order-wise tight in terms of L, µ. In addition, we show that the competitive ratio of any online algorithm is at least max{Ω(L), Ω(pLµ )} when the switching cost is quadratic. For the linear switching cost, the competitive ratio of the OMGD algorithm is shown to depend on both the path length and the squared path length of the problem instance, in addition to L, µ, and is shown to be order-wise, the best competitive ratio any online algorithm can achieve. Copyright is held by author/owner(s).

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

Availability-Aware VNF Placement for uRLLC Applications in MEC-Enabled 5G Networks 17

Availability-Aware VNF Placement for uRLLC Applications in M...

引用

17th IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2023

作者： Bera, Samaresh Indian Institute of Technology Department of Computer Science and Engineering Jammu181221 India

ISBN: (纸本)9798350307672

In this paper, we study the VNF placement problem in MEC-enabled 5G networks to meet the stringent reliability and latency requirements of uRLLC applications. We pose it as a constrained optimization problem, which is NP-hard, to maximize the total reward obtained by a network service provider by serving uRLLC service requests. We propose an approximated randomized rounding approach to solve the NP-hard optimization problem in polynomial time. We prove that the proposed randomized approach achieves performance guarantees while violating the resource constraints in a bounded way. Furthermore, we present a greedy-heuristic approach to tackle the violations in the resource constraints. Simulation results show the proposed approach yields close-to-optimal performance. Specifically, the total reward is within 5% and 10% of the optimal solution using the proposed randomized rounding and greedy approaches, respectively. © 2023 IEEE.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

Boosting cervical cancer detection with a multi-stage architecture and complementary information fusion

引用

Soft Computing 2025年第2期29卷 1191-1206页

作者： Sahoo, Pranab Saha, Sriparna Sharma, Saksham Kumar Mondal, Samrat Computer Science and Engineering Indian Institute of Technology Patna India Computer Science University of Maryland Baltimore CountyMD United States

Cervical cancer is one of the most fatal and prevalent illnesses affecting women globally. Early detection of cervical cancer is crucial for effective treatment. Pap smear tests are commonly used, but population-based screening is time-consuming, expensive, and requires expert physicians. computer-Aided Diagnosis (CAD) has shown promise in addressing this challenge. However, accurately predicting the disease using a single model can be difficult due to the complex data patterns involved. This research proposes a multi-stage architecture to improve cervical cancer screening. Initially, three pre-trained models are employed for image classification, after which the proposed advanced fusion technique is applied to combine the predictions. Additionally, we introduce a filtering approach in the third stage to refine the predictions. Unlike traditional fusion methods, the proposed architecture considers the confidence score of the base classifiers in making the final predictions on test samples. To enhance the performance of the models, we incorporate advanced augmentation techniques, including CutMix, CutOut, and MixUp. We assessed the performance of the proposed framework using a 5-fold cross-validation technique on two benchmark datasets. We evaluated the performance of the proposed framework through 5-fold cross-validation on two benchmark datasets. Remarkably, our framework achieved a classification accuracy of 97.62% and an F1-score of 97.64% on the SIPaKMeD dataset, demonstrating its effectiveness in accurately categorizing various cell types in the dataset. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Cervical cancer computer-aided detection Deep learning Ensemble learning

来源：评论

学校读者我要写书评

暂无评论

Robust Deep Convolutional Solutions for Identifying Biotic Crop Stress in Wild Environments

IEEE Transactions on AgriFood Electronics

引用

IEEE Transactions on AgriFood Electronics 2024年第2期2卷 497-508页

作者： Pal, Chiranjit Mukherjee, Imon Chatterji, Sanjay Pratihar, Sanjoy Mitra, Pabitra Chakrabarti, Partha Pratim Indian Institute of Information Technology Kalyani Department of Computer Science and Engineering Kalyani741235 India Indian Institute of Technology Kharagpur Department of Computer Science and Engineering Kharagpur721302 India

In the realm of agricultural automation, the precise identification of crop stress holds immense significance for enhancing crop productivity. Existing methods primarily focus on controlled environments, which may not accurately reflect field conditions. Field-based leaf image analysis poses challenges due to varying image quality and sunlight intensity. Moreover, the complexity of crop stress images, with their random lesion distribution, diverse symptoms, and complex backgrounds, further complicates the analysis. To overcome these limitations, a lightweight hybrid convolutional neural network has been developed. This system integrates the powerful three-deep blocks model with an autoencoder running in parallel to highlight regions of crop stress effectively. To support this approach, we have introduced the indian Rice Disease Dataset (IRDD) with labeled images. The proposed system reports an average true positive rate (TPR) of 0.8766 and an average positive predicted value of 0.8720 on IRDD, which are higher than other state-of-the-art crop disease detection models. The system is validated on benchmark datasets, yielding significant results: TPR of 0.9870 (rice), 0.9985 (tomato), and 0.8559 (corn). Furthermore, the proposed model outperforms recent state-of-the-art works on the benchmark PlantDoc dataset, showing its effectiveness in generalizing plant disease identification tasks. Finally, an ablation study has been carried out to explore the importance of the two parallel branches. Overall, this study acts as a bridge between advanced science and practical application, showcasing how interdisciplinary automation could revolutionize crop disease identification, improve agricultural efficiency, and reshape broader industrial practices. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：