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A Multi-Scale Learning Assisted Neural Network for Improved Object Detection in Complex Environments 9

A Multi-Scale Learning Assisted Neural Network for Improved ...

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9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Karthikayani, K. Vadlamani, Subramanyam M. Prasad, M.V.Siva Thatipudi, Jayendra Gopal Kalaivaani, P.C.D. Upadhyay, Shrikant Srm Institute of Science and Technology Chennai India Anurag engineering college Department of Cse Kodad India University of North Texas Dept. of Computer Science United States Kongu Engineering College Dept of Cse Perundurai638060 India Mlr Institute of Technology Department of Ece Hyderabad India

ISBN: (纸本)9798350377972

Object detection in complex environments presents significant challenges due to the variability in object scales, occlusions, and cluttered backgrounds. This paper proposes a Multi-Scale Learning Assisted Neural Network designed to improve object detection accuracy in such scenarios. The proposed model integrates multi-scale learning, hybrid attention mechanisms, and an advanced feature fusion strategy to enhance its ability to detect objects across various scales and complexities. The model was evaluated against nine state-of-the-art object detection models, including YOLOv4, Faster R-CNN, SSD, EfficientNet, RetinaNet, CenterNet, Cascade R-CNN, FCOS, and Mask R-CNN. Experimental results demonstrate that the proposed model outperforms existing models, achieving an accuracy of94.25%, precision of93.50%, recall of92.70%, and an F1-score of93.10%. Additionally, the model exhibits a balanced trade-off between inference time and model size, making it suitable for real-world applications where performance and resource efficiency are critical. The high IoU (87.50%) and mAP (89.20%) scores further validate the model's robustness in accurately detecting and localizing objects in complex environments. This study highlights the potential of the proposed model to significantly improve object detection tasks, particularly in challenging and dynamic real-world scenarios. © 2024 IEEE.

关键词： Contrastive Learning

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Explainable Multiclass Blood Cell Classification: Combining Custom CNNs with SHAP

Explainable Multiclass Blood Cell Classification: Combining ...

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International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Md. Ismiel Hossen Abir Shantanu Dey Anik Hasibul Islam Peyal Dept. of Computer Science & Engineering International Standard University Dhaka Bangladesh Dept. of Software Engineering Daffodil International University Birulia Savar Dhaka Bangladesh Dept. of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Blood cell classification is a crucial task in medical diagnostics. This work can identify different blood cell types that play essential roles in the immune system and overall body function. This research introduces a custom Convolutional Neural Network (CNN) model with SHAP for explainable multiclass classification of blood cell images. We classify eight types of blood cells—basophil, eosinophil, erythroblast, immunoglobulin (Ig), lymphocyte, monocyte, neutrophil, and platelet. An ablation study was conducted to optimize the CNN architecture. We compared its performance with eleven transfer learning models, including VGG16, ResNet101, and EfficientNet variants. Our model achieved 92.60% accuracy while maintaining lower complexity. The use of SHAP provides transparency by highlighting crucial features in the model’s decision-making process.

关键词： Training Accuracy Microprocessors Transfer learning Lymphocytes computer architecture Convolutional neural networks Medical diagnosis Blood Testing

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Data Sovereignty Provision Blockchain for Remote Healthcare Service 6

Data Sovereignty Provision Blockchain for Remote Healthcare ...

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6th International Conference on Information Systems and computer Networks, ISCON 2023

作者： Ryu, Hyunho Kim, Hyunsung Agarwal, Saurabh Sharma, Dilip Kumar Kapito, Beaton Ali, Patrick Kyungil University Dept. of Smart Security Gamasilgil 50 Kyungsan Kyungbuk Korea Republic of Amity University Uttar Pradesh Dept. of Computer Science and Engineering Noida201313 India GLA University Dept. of Computer Science and Engineering Mathura281406 India University of Malawi Mathematical Sciences Department P.O.Box 280 Zomba Malawi

ISBN: (纸本)9798350346961

Remote healthcare services provide more opportunities for communication between doctors and patients, strengthening their relationships and improving patient satisfaction and loyalty. However, those services face specific security and privacy challenges that constrain growth. Furthermore, patients' information is scattered in several hospitals with various formats, which does not provide the data sovereignty of patients. Data sovereignty is a way for any service to control or regain its data. This paper proposes a privacy-preserving blockchain for remote healthcare services to solve these issues. There is only one database of patient electronic health records in our data structure, and various hospitals could use it. The proposed data structure keeps the patient's electronic health records and the doctor's diagnosis and prescription data separate. Each entity in our system has different access rights to its role. The proposed system is based on some security primitives, including pseudonym policy, delegation, data encryption, and digital signature, depending on the privacy requirements. The proposed blockchain could be a solution against the previous centralized system and provide remote healthcare services' data sovereignty, privacy, and security.. © 2023 IEEE.

关键词： Blockchain

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Discovering Efficient Fused Layer Configurations for Executing Multi-Workloads on Multi-Core NPUs

Discovering Efficient Fused Layer Configurations for Executi...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Younghyun Lee Hyejun Kim Yongseung Yu Myeongjin Cho Jiwon Seo Yongjun Park Dept. of Artificial Intelligence Hanyang University Dept. of Computer Science and Engineering Yeonsei University Dept. of Computer Science Hanyang University SAPEON Korea Inc

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

As the AI industry grows rapidly, Neural Processing Units (NPUs) have been developed to deliver AI services more efficiently. One of the most important challenges for NPUs is task scheduling to minimize off-chip memory accesses, which may occur significant performance overhead. To reduce memory accesses, multiple convolution layers can be fused into a fused layer group, which offers numerous optimization opportunities. However, in most Convolutional Neural Networks (CNNs), when multiple layers are fused, the on-chip memory utilization of the fused layers gradually decreases, resulting in non-flat memory usage. In this paper, we propose a scheduling search algorithm to optimize the fusion of multiple convolution layers while reducing the peak on-chip memory usage. The proposed algorithm aims to find a schedule that simultaneously optimizes execution time and peak on-chip memory usage, despite a slight increase in off-chip memory accesses. It organizes the search space into a graph of possible partial schedules and then finds the optimal path. As a result of the improved on-chip memory usage, multiple workloads can be executed on multi-core NPUs with increased throughput. Experimental results show that the fusion schedule explored by the proposed method reduced on-chip memory usage by 39%, while increasing latency by 13%. When the freed on-chip memory was allocated to other workloads and the two workloads were executed concurrently in a multi-core NPU, a 32% performance improvement could be achieved.

关键词： Industries Schedules Job shop scheduling Convolution Processor scheduling Throughput System-on-chip

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Investigating Requirements and Expectations of Wearable Telexistence Robotic Systems

Investigating Requirements and Expectations of Wearable Tele...

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IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)

作者： Abdullah Iskandar Mohammed Al-Sada Osama Halabi Tatsuo Nakajima Dept. of Computer Science and Engineering Waseda University Tokyo Japan Dept. of Computer Science and Engineering Qatar University Doha Qatar

Telexistence refers to various technologies that enable a high sense of embodiment and interaction capabilities with remote environments. Although numerous telexistence systems have been explored in previous works of literature, no prior studies have investigated the usability of telexistence systems for daily use. Therefore, this study focuses on Piton, which is a novel wearable telexistence robot which has a high degree of freedom in a snake-shaped design. Piton offers a unique opportunity for remote interaction and manipulation in diverse environments, owing to its flexible movement, which enables users to adapt to various scenarios with ease. The robot's wearability is also an essential feature that allows the user to wear it as a backpack. However, despite its promising features, deeper investigation is necessary to explore potential use cases for Piton in users' daily lives and the challenge of Piton.

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Cybersecurity for Industrial IoT: A Review on Vulnerabilities and Attacks

Cybersecurity for Industrial IoT: A Review on Vulnerabilitie...

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International Conference on Electronics, Materials engineering and Nano-Technology (IEMENTech)

作者： Reetu Kumari Sunil Kumar Amandeep Kamlesh Dutta Aparna Kumari Dept. of Computer Science & Engineering Guru Jambheshwar University of Science and Technology Hisar (Haryana) India Dept. of AI & Data Science Guru Jambheshwar University of Science and Technology Hisar Haryana India Dept. of Computer Science & Engineering National Institute of Technology Hamirpur Himachal Pardesh India Dept. of Computer Science & Engineering Institute of Technology Nirma University Ahmedabad Gujarat India

ISBN: (数字)9798331520762

ISBN: (纸本)9798331520779

Internet has evolved from a network of connecting people to a network of connecting things, leading to a more complex and sophisticated network of Industrial Things, known as Industrial IoT (IIoT) today. This evolution has revolutionized the traditional Industrial system into real-time smarter systems that enhanced overall efficiency and productivity. Despite its benefits, the interconnected nature of IIoT, expanded the attack surface, exposing the systems to new crucial and complex cybersecurity threats. Several real time attacks on various industries as mentioned in this paper and the increasing cybersecurity cost over the years, clearly states the need of robust security solutions. To deeply understand the cybersecurity aspect, we provided a comprehensive study of attacks and vulnerabilities in this paper. In this paper, we did a indepth study of various IIoT related severe attacks and aspects related to these attacks, like vulnerabilities, impacts, potential solutions etc. We also provided future research directions to help the research community, to work upon and develop more robust and efficient cybersecurity solutions.

关键词： Industries Productivity Reviews Prevention and mitigation Intrusion detection Interconnected systems Real-time systems Internet computer security Industrial Internet of Things

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AutoFlows: Inferring Message Flows from System Communication Traces

AutoFlows: Inferring Message Flows from System Communication...

引用

IEEE International Symposium on Quality Electronic Design

作者： Bardia Nadimi Hao Zheng Dept. Computer Science and Engineering University of South Florida Tampa United States

ISBN: (数字)9798331509422

ISBN: (纸本)9798331509439

This paper proposes a novel method for automatically inferring message flow specifications from the communication traces of a system-on-chip (SoC) design that captures messages exchanged among the components during a system execution. The inferred message flows characterize the communication and coordination of components in a system design for realizing various system functions, and they are essential for SoC validation and debugging. The proposed method relieves the burden of manual development and maintenance of such specifications on human designers. Our method also uses a new accuracy metric, acceptance ratio, to evaluate the quality of the mined specifications instead of the specification size often used in the previous work, enabling more accurate specifications to be mined. Furthermore, this paper introduces the concept of essential causalities to enhance the accuracy of the message flow mining and accelerate the mining process. The effectiveness of the proposed method is evaluated on both synthetic traces and traces generated from executing several system models in GEM5. In both cases, the proposed method achieves superior accuracies compared to a previous approach. Additionally, this paper includes some practical use cases.

关键词： Measurement Deep learning Accuracy Runtime Protocols Debugging Manuals System-on-chip Maintenance System analysis and design

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Unraveling Customer Sentiment in Indian Fashion E-Commerce: A BERT-Based Approach

Unraveling Customer Sentiment in Indian Fashion E-Commerce: ...

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International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

作者： Oneeka Taneja Kuppili Raja Satya Alpana Deepa C Rathod Anaum Fathima M R Vishalakshi Prabhu H Computer Science (Data Science) R. V. College of Engineering Bangalore India Dept. of Computer Science R. V. College of Engineering Bangalore India

ISBN: (数字)9798331505462

ISBN: (纸本)9798331505479

With the surge of e-commerce growth in India, it has become very necessary for brands to understand the sentiments of customers so that they can improve their offerings and remain in competition. In this study, the transformer-based model, namely BERT is used for conducting sentiment analysis of customer reviews related to famous Indian clothing brands such as Myntra, Ajio and Tata Cliq. Our research utilizes BERT contextual embeddings for the capture of opinions and emotions in customer feedback. In this paper, we will look to prove the efficiency of BERT in sentiment classification regarding Indian fashion e-commerce by analyzing a large corpus of reviews from these popular platforms, as well as compare its accuracy to DistilBERT. The study will identify how this approach extracts meaningful insights from unstructured text data that turn very useful to the brands for understanding customer satisfaction and improvement areas. Sentiment analysis of online cloth industry is one of the rarely explored field and our paper introduces this idea, specifically for the Indian demographic. Our results contribute to the developing literature of sentiment analysis in the Indian e-commerce domain and illustrate some of the many ways in which state-of-the-art natural language processing techniques are put to work in retail.

关键词： Industries Sentiment analysis Reviews Customer satisfaction Clothing Transformers Electronic commerce Data mining Surges Information technology

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A Design Framework for Preserving Cultural Heritage with AR Technology—An Innovative Exploration on Ethnic Motifs and Its Symbolism of the Naga Tribes 9th

A Design Framework for Preserving Cultural Heritage with AR ...

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9th International Conference on Research into Design, ICoRD 2023

作者： Roy, Susmita Singh, Pankaj Pratap Padun, Abhijit Dept. of Multimedia Communication and Design CIT Kokrajhar Assam BTAD Kokrajhar India Dept. of Computer Science and Engineering CIT Kokrajhar Assam BTAD Kokrajhar India

ISBN: (纸本)9789819902927

The strong sense of immersion and interaction of advanced technology have an immense contribution towards cultural preservation in this digital era. Presently, the augmented technology is preferable and very popular from the aspect of the cultural heritage domain to revive and preserve cultural assets. This article presents a design-based framework to revive the original essence and significance of ethnic motifs and symbolism embedded in the Naga woven fabrics with Augmented Reality (AR) technology. This design framework proposes a smartphone-based application to decodes and interpret the meaning and symbolism of the motifs & patterns from Naga traditional woven fabric. This framework uses AR technology to scan and extract motifs & patterns from the traditional woven fabrics, thereby displaying the story on the visual screen. The information related to the motifs and patterns is delivered with authentic interpretations of the Naga ancient core. This application further explores the possibility of implementing it for cultural education which may create a unique identity of the hand woven fabrics of Naga tribes on digital platform. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Augmented reality

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Leveraging Artificial Intelligence for Colon Cancer: Trends, Challenges and Innovations

Leveraging Artificial Intelligence for Colon Cancer: Trends,...

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Automation and Computation (AUTOCOM), International Conference on

作者： Sakshi Takkar Manik Rakhra Dept. of Computer Science and Engineering Lovely Professional University Phagwara Punjab India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Artificial Intelligence (AI) has made huge enhancements in colon cancer research through its methods for diagnosis, treatment, and custom detection of one of the most common and fatal cancers suffered globally. Through AI deep learning and machine learning methods, tremendous possibilities have been realized in automating, for example, polyp detection in colonoscopy images, cancer classification from histopathological slides, and even predicting disease treatment outcomes. The current direction is towards transfer learning, hybrid model building and AI applications in surgery robots aimed at more accurate diagnosis and treatment procedures. Besides them, however, they have serious disadvantages, access to computer learning systems and datasets are limited, AI models come without explanation, embedding of artificial intelligence into clinical practices becomes troublesome. In future development, emphasize should be on creating databases, explainable ethics AI approaches, building bridges between developers and practitioners in medicine. The objective of the paper is how to incorporate research that has been done in moving colon cancer AI systems into practice, understanding the AI satellites put on colon cancer research.

关键词： Deep learning Ethics Technological innovation Computational modeling Buildings Transfer learning Surgery Colorectal cancer Data models Artificial intelligence

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