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Food Adulterant Detection Using Hyperspectral Imaging System in Okra 5

Food Adulterant Detection Using Hyperspectral Imaging System...

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5th International conference on Sustainable communication Networks and Application, ICSCNA 2024

作者： Shiny, J. John Haranya, S. Sameeha, A. Sivanithi, P. Velammal College of Engineering and Technology Department of Information Technology Madurai India

ISBN: (纸本)9798331530013

The adulteration of food products in relation to food safety and quality assurance for the project results in serious consequences with regards to consumer health and market integrity. This work attempts to achieve a reliable and rapid means of detecting adulteration in food by use of hyperspectral imaging (HSI) system. Given its potential in capturing and analyzing a wide spectrum of light outside the visible range, hyperspectral imaging becomes a very great tool in identifying and quantifying adulterants not easily detectable with visual or chemical methods. A collection of comprehensive set of hyperspectral images taken from both pure and adulterated okra (lady's finger) samples were processed in the data extraction process of spectral signatures and other important features which will differentiate the adulterated okra from the non-adulterated okra. Advanced image processing techniques such as Principal Component Analysis (PCA) was applied to extract the features, augment by applying noise injection and rotation techniques. In addition to this, superior machine learning algorithms like Conventional Neural Network (CNN) were used for hyperspectral data analysis and classification of the okra samples. The main focus is to develop computational models that could classify the level of okra adulteration with better accuracy and quantify the same. Three CNN models (1D CNN, 2D CNN and 3D CNN) were applied to the samples. It was inferred that 1D CNN model classified the okra samples more accurately with a test accuracy of 0.81 when compared to other models 2D and 3D. © 2024 IEEE.

关键词： Convolutional Neural Network (CNN) Food Adulteration Hyperspectral Imaging (HSI) Principal Component Analysis (PCA)

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Mathematical Modeling of Binding Semantic Memory with visual information

Mathematical Modeling of Binding Semantic Memory with Visual...

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International conference on information and communication Technology Convergence (ICTC)

作者： Hideyuki Kato Haruki Terakawa Yoshihiro Yonemura Yuichi Katori Faculty of Science and Technology Oita University Oita Japan Graduate School of Engineering Oita University Oita Japan School of Systems Information Science Future University Hakodate Hokkaido Japan

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

This study investigates visual information processing and its integration with semantic memory with a hierarchical predictive coding with reservoir computing model. The model explores how visual elements like color and shape interact with semantic memory, focusing on the reverse Stroop effect. The model processes images of gendered toilet symbols, demonstrating that East Asian models, which use color cues for gender identification, exhibit quicker recognition than other models. The perception is accurate for images with consistent color and shape information but inaccurate for images with conflicting color and shape information. The results illustrate that the model effectively simulates the reverse Stroop effect, revealing insights into visual and semantic memory interactions.

关键词： visualization Image recognition Image color analysis Shape Computational modeling Semantics Reservoir computing Predictive models Predictive coding Mathematical models

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Secure Image Authentication and Copyright Protection Using Integer Wavelet Transform 15

Secure Image Authentication and Copyright Protection Using I...

引用

15th International conference on Software, Knowledge, information Management and Applications, SKIMA 2023

作者： Ernawan, Ferda Onn, Ng Ching Bakar, Suraya Abu Zarlis, Muhammad Universiti Malaysia Pahang Al-Sultan Faculty of Computing Abdullah Pekan Malaysia Bina Nusantara University Information System Management Department Jakarta Indonesia

ISBN: (纸本)9798350316551

Widespread usage of the internet and digital communication technologies, multimedia data may be vulnerable to piracy as unauthorized users can easily alter multimedia data such as images. In this study, IWT and SVD based on human visual characteristics are proposed, to embed the watermark in the image, making it more resistant to attacks while low distortion on image quality. The watermarked image is then embedded with authentication bits obtained from the image content of 3x3 block pixels. The authentication bits are embedded into the LSB of pixel to ensure that RGB images can be authenticated if there is any tampering attacks. Various geometrical, compression, image processing attacks and tampering attacks are used to test the effectiveness of the proposed approach. Hence, the test results are compared to other dual watermarking systems. The results of these experiments show that our approached can accurately detect tampering in most cases, even when the changes made to the image affect a small number of blocks. Additionally, we found that our approach provides high robustness, even when image processing attacks are extensive. The results demonstrate the PSNR value of about 48 dB, effectiveness of our authentication approach obtained accuracy of 0.98 for tampering attacks and show that it is a promising technique for robustness of embedded copyright. © 2023 IEEE.

关键词： Image watermarking

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Unconventional to Automated Attendance Marking Using Image processing 4th

Unconventional to Automated Attendance Marking Using Image P...

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4th International conference on Advances in information communication Technology and Computing, AICTC 2022

作者： Pradhan, Abhiujjwal Pal, Ritu Kumar, Sachin Koli, Sakshi Kalra, Bharti Nawaz, Waris Computer Science Department Tula’s Institute Dehradun Dehradun India

ISBN: (纸本)9789811998874

The traditional method of raising your hand in a classroom to say "present ma’am" or "yes ma’am" or whatever other things you would say is kind of fading away, Image processing is becoming increasingly important in the digital world. Magicians play an important function in today's information era. visual processing is necessary in the area of biometrics to identify a individual whose biometric image has already been saved in a database. Image based biometrics, such as faces, biometrics, and eyes, need image processing and pattern recognition algorithms. To perform correctly, an image-based biometric system requires a sample image of the user's biometric that is highly clear and unadulterated. This study proposes the development of a system that automated stamps students’ attendance using automated image render ways such as facial detection and identification. Face recognition is challenging due to factors such as face pattern, orientation, shape, varied patterns, and the complexity of face expression. Using multiple datasets, the system is taught to identify the face-representing pattern (positive pattern of face) and set it apart from the surroundings (critical pattern of facial expression) environment. The major goal is to provide an autonomous platform for recognising faces in video, as well as documenting student attendance by identifying them from their various face patterns. This aids in the automatic maintenance and management of the attendance system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Biometrics

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Unsupervised Modality Adaptation with Text-to-Image Diffusion Models for Semantic Segmentation 38

Unsupervised Modality Adaptation with Text-to-Image Diffusio...

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38th conference on Neural information processing Systems, NeurIPS 2024

作者： Xia, Ruihao Liang, Yu Jiang, Peng-Tao Zhang, Hao Li, Bo Tang, Yang Zhou, Pan East China University of Science and Technology China Vivo Mobile Communication Co. Ltd. China Peng Cheng Laboratory China Singapore Management University Singapore

Despite their success, unsupervised domain adaptation methods for semantic segmentation primarily focus on adaptation between image domains and do not utilize other abundant visual modalities like depth, infrared and event. This limitation hinders their performance and restricts their application in real-world multimodal scenarios. To address this issue, we propose Modality Adaptation with text-to-image Diffusion Models (MADM) for semantic segmentation task which utilizes text-to-image diffusion models pre-trained on extensive image-text pairs to enhance the model's cross-modality capabilities. Specifically, MADM comprises two key complementary components to tackle major challenges. First, due to the large modality gap, using one modal data to generate pseudo labels for another modality suffers from a significant drop in accuracy. To address this, MADM designs diffusion-based pseudo-label generation which adds latent noise to stabilize pseudo-labels and enhance label accuracy. Second, to overcome the limitations of latent low-resolution features in diffusion models, MADM introduces the label palette and latent regression which converts one-hot encoded labels into the RGB form by palette and regresses them in the latent space, thus ensuring the pre-trained decoder for up-sampling to obtain fine-grained features. Extensive experimental results demonstrate that MADM achieves state-of-the-art adaptation performance across various modality tasks, including images to depth, infrared, and event modalities. We open-source our code and models at https://***/XiaRho/MADM. © 2024 Neural information processing systems foundation. All rights reserved.

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A Framework of Ensemble CNN Models for Real-Time Sign Language Translation 14

A Framework of Ensemble CNN Models for Real-Time Sign Langua...

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14th International conference on Software, Knowledge, information Management and Applications, SKIMA 2022

作者： Xian Chung, Hao Hameed, Nazia Clos, Jeremie Hasan, Md Mahmud School of Computer Science University of Nottingham Nottingham United Kingdom School of Computer and Information Systems Anglia Ruskin University Cambridge United Kingdom

ISBN: (纸本)9781665493345

American sign language (ASL) is a natural language to minimize communication barrier for the people suffering from hearing and speech impairment. However, sign languages are not a common form of communication in society, and it is lacking a sign language translator to ease the communication. Hence, this research proposes an improved visual-based communication framework to translate ASL alphabets in real-time. The proposed framework consists of different steps i.e., image pre-processing, hand segmentation with U-Net, data-augmentation techniques, and classification of American sign language. A n ensemble classification model i s proposed where V GG19, R esNet-50 and MobileNet are used as base models, and 2 fully connected layers are used as meta model. The proposed approach achieved 99.86% accuracy and performed better when compared with existing literature. © 2022 IEEE.

关键词： Audition

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E-commerce Website based on Graphics and Image processing Technology (IPT) 22

E-commerce Website based on Graphics and Image Processing Te...

引用

6th International conference on Graphics and Signal processing, ICGSP 2022

作者： Dang, Mihua Liu, Hongli Xi'an Traffic Engineering Institute Shaanxi Xi'an China

ISBN: (纸本)9781450396370

With the rapid development of information technology, e-commerce has gradually entered thousands of households from high technology. E-commerce website (ECW) have become an important bridge for daily communication between enterprises and between enterprises and consumers. Image is one of the most important and commonly used information of human beings;Digital IPT is the process of converting image signal into digital format and processing it by computer. This paper studies and analyzes the application of graphics and IPT in the construction of ECW, discusses the graphics and IPT and the result design process of ECW, and tests the network name's views on the website construction proposed in this paper through online questionnaire experiment. The results show that 84% of Internet users using graphics and IPT in the construction of ECWs will make people more willing to browse websites, and 76% said that the visual effect of web pages is good, while websites without graphics and IPT have little effect on improving shopping desire, and only 61% of Internet users said they are willing to browse websites. It is verified that the application of graphics and IPT in the construction of ECW in this paper is conducive to improve the browsing volume of the website, and can also improve the visual aesthetic sense for Internet users, which is welcomed by the audience. © 2022 ACM.

关键词： Websites

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Defect Recognition on Single Layer Bare Printed Circuit Boards for Quality Control and visual Inspection: A Low-Sample-Size Deep Transfer Learning Approach 9

Defect Recognition on Single Layer Bare Printed Circuit Boar...

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9th International conference on Signal processing and Intelligent Systems, ICSPIS 2023

作者： Austria, Yolanda D. Fajardo, Arnel C. Technological Institute of the Philippines Graduate School Program Quezon City Philippines Isabela State University College of Computing Science Information and Communication Technology Isabela Cauayan City Philippines

ISBN: (纸本)9798350369922

Defect detection is a critical component in ensuring the highest quality of printed circuit board manufacture. The work investigates the application of transfer learning to identify YOLOv8 design flaws. The YOLOv8 model performs exceptionally well, with mean Average Precision (mAP) of 98.3%, Precision of 98.6%, and Recall of 96.0%. Numerous datasets provide high detection rates across a range of fault types following thorough testing and inference. This extensive evaluation demonstrates the robustness of the model by reliably identifying Fissure, Mousebite, EC-Short, MC-Spur, Breakout, Pinhole, and Copper defects. The study emphasizes how the YOLOv8 design can identify flaws, providing a dependable and effective way to guarantee the dependability and caliber of printed circuit boards throughout the production process. The foundation for utilizing YOLOv8 in industrial quality control is established by this study, which holds significant potential for improving defect detection and quality control in the manufacturing industry. © 2023 IEEE.

关键词： Printed circuit boards

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Brain communication: A system where to investigate and re-engineer human communication and learning processes 10

Brain Communication: A system where to investigate and re-en...

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10th International conference on information Technology and Quantitative Management, ITQM 2023

作者： Córdova, Felisa Hernán Díaz, M. School of Engineering Faculty of Engineering University San Sebastián Bellavista 7 Recoleta Santiago8420000 Chile Department of Mathematics and Computer Science Faculty of Science University of Santiago de Chile Av. Libertador Bernardo O'Higgins 3363 Estación Central Santiago9170002 Chile

A method for detecting and monitoring the long-term time course of brain processes is described for two different conditions: i) A abbreviated version of a visual problem-solving IQ (Intelligent Quotient) Raven test and ii) A perceptual video task consisting of watching a sequence of (3 minutes each) 5 movie genera: animation, war, romance, violence and thriller. The method consisted of the analysis of the grayscale pixel values of the spectrographic image, generated by a Fast Fourier Transform (FFT), applied over the amplitude v/s time domain of the electroencephalographic (EEG) signal recorded during the execution of the test/task. Results show a high-resolution tool for detecting and monitoring brain signals in very narrow frequency range (0,05 Hz) and time (100 ms). Subject-dependent individual differences (N=5) are evident and a number up to 10 frequency communication channels can be detected in narrow frequency range of 0,5 Hz. Combining both aspects of these tool, high resolution of the frequency range, and the subject-dependent individual differences found in the execution of the test/task, we plan to use this information to classify subjects according problem-solving and perceptual brain processing differences and learning preferences. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Tenth International conference on information Technology and Quantitative Management.

关键词： Fast Fourier transforms

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Pixel Processor Arrays For Low Latency Gaze Estimation

Pixel Processor Arrays For Low Latency Gaze Estimation

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IEEE conference on Virtual Reality and 3D User Interfaces (IEEE VR)

作者： Bose, Laurie Chen, Jianing Carey, Stephen J. Dudek, Piotr Pixelcore Res Ltd Manchester Lancs England Univ Manchester Manchester Lancs England

ISBN: (纸本)9781665484022

We demonstrate the use of a Pixel Processor Array (PPA) vision sensor for achieving rates of over 10,000 Hz, with processing latency below 0.1 ms, in a gaze tracking application, performing image processing directly upon the sensor itself with minimal external computation. Each pixel processing element of the PPA sensor is capable of light sensing, data storage and computation, allowing various visual processing to be performed efficiently at the point of light capture. We demonstrate how information such as pupil location, size, and LED reflections upon the eye's surface can be extracted by the PPA, along with a simple gaze tracker using pupil location. By extracting such information directly on-sensor, the data needing to be transferred from sensor to external processing is reduced from entire images to a hand-full of contextual bytes, this provides significant saving in terms of power, time and allows for frame-rates far exceeding traditional camera sensors.

关键词： Human-centered computing Human computer interaction (HCI) Interaction paradigms Virtual reality Hardware communication hardware, interfaces and storage Sensors and actuators

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