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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Akter, Tahmina Majumder, Avishek Mahmud, Tanjim Habib, Israt Binteh Hossain, Mohammad Shahadat Andersson, Karl Port City International University Dept. of Computer Science and Engineering Chittagong Bangladesh Rangamati Science and Technology University Dept. of Computer Science and Engineering Rangamati4500 Bangladesh International Islamic University Chittagong Dept. of Computer Science and Engineering Chittagong Bangladesh University of Chittagong Dept. of Computer Science and Engineering Chittagong4331 Bangladesh Luleå University of Technology Cybersecurity Laboratory Luleå97187 Sweden

ISBN: (纸本)9798350370249

In the rapidly advancing field of computer vision, object detection has become crucial for various applications, including animal tracking, face detection, and surveillance systems. This study investigates the efficacy of contemporary object detection methodologies by evaluating the performance of the You Only Look Once (YOLO) models and TensorFlow Model Zoo architectures for animal tracking. YOLO models, known for their ability to process entire images in real-time and predict bounding boxes and class probabilities simultaneously, offer significant advantages over traditional methods such as Convolutional Neural Networks (CNNs) and Fast R-CNNs. This paper compares the performance of YOLOv5 and YOLOv7, alongside TensorFlow-based models like Faster R-CNN ResNetv152 and SSD ResNet101, using a dataset of animal images. Our findings reveal that YOLOv5 outperforms other models with a mean average precision (mAP) of 9 7.5%, demonstrating superior accuracy and efficiency in object detection tasks. YOLOv7 also shows strong performance with an mAP of 96.7%, while TensorFlow Model Zoo's Faster R-CNN and SSD models lag behind with mAPs of 81.9% and 81.6%, respectively. The results highlight the significant advancements in deep learning and object detection algorithms, particularly the advantages of YOLO's architecture in handling complex detection tasks in real-world scenarios. © 2024 IEEE.

关键词： Convolutional neural networks

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Call Translator with Voice Cloning Using Transformers 9

Call Translator with Voice Cloning Using Transformers

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9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Khan, Nawaz Fateen Hemanth, Nandan Goyal, Navyae Pranav, K.R. Agarwal, Pooja Pes University Computer Science Engineering Dept. Bangalore India

ISBN: (纸本)9798350394474

Voice Cloning employs technology and algorithms to create an artificial or synthetic reproduction of a person's voice. To understand and mimic the distinct vocal qualities of the target speaker, including tone, pitch, cadence, and pronunciation, a machine learning model must be trained on audio samples of the speaker. This project presents itself as a revolutionary approach to the enduring problem of successful cross-lingual interactions, the paper's novel approach to speech-to-speech machine translation that incorporates voice cloning. This method allows us to synthesize speech in the target language while maintaining the original speaker's vocal characteristics. The model algorithms such as Whisper AI(WER 5% for transcription, No-Language-Left-Behind-200(44% more accurate than other models) for translation, Tacotron for speech synthesis and multiple transformers for voice cloning will be incorporated. The Voice Cloning model operates effectively on unseen voices, transcending the limitations of voice cloning will be incorporated. The voice cloning model operates effectively on unseen voices, transcending the limitations of relying solely on pre-trained models. The model successfully clones users' voices in a different language with an approximate latency of 10 seconds. © 2024 IEEE.

关键词： Speech synthesis

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Optimal Trajectory Planning of an Omni-directional Mobile Manipulator for Obstacle Avoidance

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Transactions of the Korean Institute of electrical Engineers 2023年第8期72卷 952-958页

作者： Kim, Minsu Sung, Young Whee School of Electrronic Engineering Kumoh National Institute of Technolgy Korea Republic of Dept. of Electrical Engineering and Computer Science DGIST Korea Republic of

The ultimate purpose of a mobile robot is to do some tasks in addition to moving to a desired point, so it is very natural for a mobile robot to be equipped with a manipulator. Among many types of mobile robots, omni-directional mobile robot has been very popular because it has advantages in trajectory planning and control. In this paper, we deal with an omni-directional mobile manipulator that consists of a four Mecanum wheeled mobile robot platform and a manipulator mounted on it. In general, it is very difficult to solve inverse kinematics for a mobile manipulator because it has infinite solutions. Omni-directional mobile robot platform can move in any direction and can rotate on a pivot in a plane, so we propose it to be modeled as a manipulator with two prismatic joints and one revolute joint. Then the overall omni-directional mobile manipulator can be considered as a manipulator with an (n+3) DOF manipulator if the mounted manipulator has n DOF. We propose a weighted pseudo-inverse based method to solve the inverse kinematics problem at velocity level for the omni-directional mobile manipulator. In our method, in addition to a primary task of following end-effector trajectory, a secondary task of obstacle avoidance is accomplished by maximizing a performance index that represents a distance between a link of the manipulator and an obstacle. Simulation results showed the feasibility of the proposed method. © 2023 Korean Institute of electrical Engineers. All rights reserved.

关键词： Manipulators

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Sentient Sound waves: Elevating Emotional Communication with AI-Generated Speech Technology 5

Sentient Sound waves: Elevating Emotional Communication with...

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5th IEEE International Conference for Emerging Technology, INCET 2024

作者： Roshan, Rahul G. Roshan, Rohit Sohan, M.H. Raj, S.M. Sutharsan Prasad, V.R. Badri Dept. of Computer Science and Engineering PES University Bangalore India

ISBN: (纸本)9798350361155

This research-based project is about a new way to put feelings into computer-generated speech. It has two stages: text emotion detection and emotional speech synthesis. In the former part, labeled text data is used to build models to spot the emotions. This model learns to change pitch, volume, and rhythm based on the given emotion. During the latter phase, the text is changed into neutral speech using text-to-speech (TTS) methods. The model is used for practice to find the emotion in the text, tagging the text with that emotion. Also, a deep-learning model known as a tacotron is employed to make an emotional-sounding speech. The model perfectly uses machine learning strategies to blend feelings into speech. This opens up possibilities for turning plain text into speech with feelings of varied emotions. The proposed system makes a novice and important contribution to natural language processing for emotion identification and deep learning for emotional speech synthesis. © 2024 IEEE.

关键词： Speech synthesis

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Enhanced Level Brain Tumor Identification Using CNN, VGG16 and ResNet Models 2

Enhanced Level Brain Tumor Identification Using CNN, VGG16 a...

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2nd IEEE International Conference on Contemporary Computing and Communications, InC4 2024

作者： Sambandam, Rakoth Kandan Jyoshna, Mallela Christ University Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350383652

The comprehension of brain growths is significantly improved through the identification and categorization of these disorders. Still, their discovery is relatively grueling due to their variability in terms of position, shape, and size. Fortunately, deep literacy has revolutionized the field and significantly improved recognition, prediction, and opinion in various healthcare areas, including brain excrescences. The main goal of this study is to thoroughly review exploration that utilizes CNN, VGG16, and RESNET infrastructures to classify brain excrescences using MRI images. The performance of these models varied significantly, with CNN, VGG16, and RESNET achieving an emotional delicacy of 99.6. Additionally, ResNet and VGG16 achieved rigor of 92.4 and 89.7 independently. Likewise, the visualization of the decision-making processes of these models has provided valuable insight into the features they prioritize. By incorporating these models into their practice, healthcare professionals have the opportunity to enhance their individual capabilities, eventually leading to improved patient outcomes. © 2024 IEEE.

关键词： Deep learning

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Benchmarking Network Functionality: Performance Evaluation of SDN Controllers on Different Network Functions 100

Benchmarking Network Functionality: Performance Evaluation o...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Monir, Md Fahad Fawad Hasan, Azwad Hoque, Md Mozammal Ahmed, Tarem Granelli, Fabrizio Independent University Dept. of Computer Science and Engineering Bangladesh University of Houston Cullen College of Engineering TX United States Dept. of Information Engineering and Computer Science Trento Italy

ISBN: (纸本)9798331517786

Network Softwarization revolutionizes infrastructure by introducing programmable network functions, leading to scalable, agile, and efficient networks. This innovation facilitates adaptable, secure Next Generation Networks, transforming connectivity. This study conducts a comparative analysis of SDN-based network functions utilizing three different controllers: Open vSwitch (OVS), OpenFlow Reference controller, and RYU, to understand their impact on packet loss and jitter. The OpenFlow Reference controller, primarily used for educational and basic experimental purposes, serves as a baseline. The OVS controller, operating within the Open vSwitch framework in Mininet, offers a practical level of network management capability, more advanced than the OpenFlow Reference controller yet not as comprehensive as the RYU Controller, a production-grade SDN controller. Our research aims to fill the gap in comparative performance analysis of these controllers, particularly in hybrid round-robin-based load balancing and firewall implementations. Recognizing the operational reality of SDN deployments, we explore both reactive and proactive modes, acknowledging that real-world applications like firewalls and load balancers often operate proactively with pre-populated rules, affecting data plane performance. The findings provide insights into each controller's effectiveness, with OVS and RYU showing enhanced capability in reducing packet loss and jitter compared to the OpenFlow Reference controller. This research not only sheds light on the functional behaviors and performance trade-offs of these controllers but also contributes to the broader SDN and NFV discourse, offering a foundation for future academic and practical advancements in the field. © 2024 IEEE.

关键词： Packet loss

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Automatic Skull Shape Completion of Defective Skulls Using Transformers for Cranial Implant Design 2

Automatic Skull Shape Completion of Defective Skulls Using T...

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2nd International Conference on Machine Learning and Data engineering, ICMLDE 2023

作者： Resmi, S. Singh, Rimjhimpadam Palaniappan, Kannappan Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Dept. of Electrical Engineering and Computer Science University of Missouri MO United States

Cranioplasty is a surgical method that restores the aesthetic and protecting function of a damaged skull by implanting material into the damaged *** and accurate design of patient specific cranial implants is very much required in the process of *** time consumption for designing and manufacturing of patient specific cranial implant has become an obstruction for cranioplasty procedures. Hence, a fully automatic and fast design of cranial implant becomes very important. The cranial implant design processmainly comprises of two steps. The former step concentrates on the automatic skull shape completion of defective skulls to fill the gaps and the cracks created in the skull. While the second step computes the difference between defective input and the completed skull for generating the implant. Currently computer aided design is used for the skull shape completion task which is a time consuming process. The application of deep learning techniques may result to faster and accurate skull shape completionwhich can be used for the design of patient specific cranial implants. This work proposes a novel approach combining 3D U-Net with Transformers for the automatic skull shape completion *** are using a vision transformer in the encoder section of the 3D U-Net architecture to consider the volumetric skull reconstruction as sequence- to-sequence prediction problem and to efficaciously grasp the global contextual information. The work also compares its performance with the famous variants of 3D U-Net deep network model namely, 3D U-Net and 3D U-Net with attention. From the values resulted for the dice coefficient metric it is clear that the proposed 3D U-Net with transformer approach performs better than the other two models on test images. © 2024 Elsevier B.V.. All rights reserved.

关键词： computer aided design

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Effects of Mismatch on IC-Equipped Programmable Metasurfaces with Multibeam Functionality

Effects of Mismatch on IC-Equipped Programmable Metasurfaces...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Kossifos, Kypros M. Georgiou, Julius Antoniades, Marco A. University of Cyprus Dept. of Electrical & Computer Engineering Nicosia Cyprus Toronto Metropolitan University Dept. of Electrical Computer & Biomedical Engineering ON Canada

ISBN: (纸本)9781665442282

Integrated circuit (IC) technology can be incorporated in programmable metasurfaces (PMSFs) and reduce their cost and power consumption while increasing their electromagnetic manipulation capabilities. Such improvements can succour the incorporation of PMSFs as a common telecommunication technology. In order for this to be realised, the reproducibility and reliability of IC-equipped PMSFs need to be addressed. A study is presented on effects of IC mismatch on the performance of a PMSF with multibeam functionality. A mismatch of 10% to 40% of the nominal IC response is used and the effects on the far field are presented. © 2023 IEEE.

关键词： Timing circuits

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RT-MDM: Real-Time Scheduling Framework for Multi-DNN on MCU Using External Memory 24

RT-MDM: Real-Time Scheduling Framework for Multi-DNN on MCU ...

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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Kang, Sukmin Lee, Seongtae Koo, Hyunwoo Chwa, Hoon Sung Lee, Jinkyu Dept. of Semiconductor and Display Engineering Sungkyunkwan University Korea Republic of Samsung Electronics Co. Ltd. Korea Republic of Dept. of Computer Science and Engineering Sungkyunkwan University Korea Republic of School of Electronic and Electrical Engineering Sungkyunkwan University Korea Republic of Dept. of Electrical Engineering and Computer Science Dgist Korea Republic of

ISBN: (纸本)9798400706011

As the application scope of DNNs executed on microcontroller units (MCUs) extends to time-critical systems, it becomes important to ensure timing guarantees for increasing demand of DNN inferences. To this end, this paper proposes RT-MDM, the first RealTime scheduling framework for Multiple DNN tasks executed on an MCU using external memory. Identifying execution-order dependencies among segmented DNN models and memory requirements for parallel execution subject to the dependencies, we propose (i) a segment-group-based memory management policy that achieves isolated memory usage within a segment group and sharded memory usage across different segment groups, and (ii) an intra-task scheduler specialized for the proposed policy. Implementing RT-MDM on an actual system and optimizing its parameters for DNN segmentation and segment-group mapping, we demonstrate the effectiveness of RT-MDM in accommodating more DNN tasks while providing their timing guarantees. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Memory management

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Leveraging Information and Communication Technology (ICT) To Combat Corruption: A Systematic Review

Leveraging Information and Communication Technology (ICT) To...

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2024 International Conference on science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Oluwambo Tolulope, Olowe Ariyo Adebiyi, Ayodele Akindeji, Kayode Landmark University Dept. of Computer Science Omuaran Nigeria Durban University of Technology Dept. of Electrical Power Engineering Durban South Africa

ISBN: (纸本)9798350358155

Corruption, a global phenomenon disproportionately affecting developing nations, undermines governance and economic development. This systematic literature review examines the role of Information and Communications Technology (ICT) in mitigating corruption. Despite conflicting evidence, ICT interventions, including transactional and transparency reforms, offer promising avenues for combating corrupt practices. The review highlights the diverse methodologies employed, with a significant focus on AI-related approaches. Collaboration among researchers, policymakers, and stakeholders is essential for developing comprehensive strategies to address corruption effectively, particularly leveraging ICT advancements. © 2024 IEEE.

关键词： Artificial intelligence

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