the correct distinction between highly realistic computer-generated (CG) images and photographic (PG) images has become an important area of research. In recent years, most of the CG image forensics methods are propos...
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Working with construction machinery necessitates that workers remain attentive to effectively survey their surroundings. the complex environment, blind spots, and limited visibility while simultaneously tackling compl...
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In recent years, the agricultural sector has encountered major challenges due to the widespread presence of plant leaf diseases, which pose serious risks to crop yields and food security. Advancements in artificial in...
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Given the exponential growth of global data, research attention has increasingly focused on content-based image retrieval. While deep learning has optimized computervision tasks, existing image search tools continue ...
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India's primary industry, agriculture, accounts for the majority of the country's GDP. Weed growth is one of the primary factors that lowers agricultural productivity. In the field, the combination of machine ...
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the proceedings contain 23 papers. the special focus in this conference is on Security and Privacy in New Computing Environments. the topics include: Consortium Blockchain Storage Optimization Based on60;Fountain C...
ISBN:
(纸本)9783031736988
the proceedings contain 23 papers. the special focus in this conference is on Security and Privacy in New Computing Environments. the topics include: Consortium Blockchain Storage Optimization Based on Fountain Codes;an Incentive Mechanism and An Offline Trajectory Publishing Algorithm Considering Sensing Area Coverage Maximization and Participant Privacy Level;Research on Face Recognition System Based on RLWE Homomorphic Encryption;feedback Feed-Forward Iterative Learning Control for Non-affine Nonlinear Discrete-Time Systems with Varying Trail Lengths;open-Closed-Loop Iterative Learning Control Based on Differential Evolution Algorithm for Nonlinear System;overview of Vehicle Edge Computing and Its Security;conFlow: Contrast Network Flow Improving Class-Imbalanced Learning in Network Intrusion Detection;anomaly Detection of Unstable Log Data Based on Contrastive Learning;An Integration-Enhanced ZNN Approach for Chaotic Combination Synchronization with External Disturbances∗;a Lightweight Anomaly Detection Method for Industrial Processes Based on Event Correlation Behavior;a Novel Polar Code-Based Key Encapsulation Mechanism with Non-permutation Equivalent Public Key;two-Stage Multi-lingual Speech Emotion Recognition for Multi-lingual Emotional Speech Synthesis;EncoderMU: Machine Unlearning in Contrastive Learning;NoCrypto: A Web Mining Behavior Detection Method Based on RGB images;image Copy-Move Forgery Detection in the Social Media Based on a Prior Density Clustering and the Point Density;detection of Speech Spoofing Based on Dense Convolutional Network;speech Emotion Recognition Based on Recurrent Neural Networks with Conformer for Emotional Speech Synthesis;Route Privacy-Preserving Authentication Scheme Based on PUF in VANETs;Stable NICE Model-Based Picture Generation for Generative Steganography;computer-Generated image Forensics Based on vision Transformer with Forensic Feature Pre-processing Module;VoIP Steganalysis Using Shallow Multiscale Convolution and
object detection based on event vision has been a dynamically growing field in computervision for the last 16 years. In this work, we create multiple channels from a single event camera and propose an event fusion me...
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ISBN:
(数字)9798331506520
ISBN:
(纸本)9798331506537
object detection based on event vision has been a dynamically growing field in computervision for the last 16 years. In this work, we create multiple channels from a single event camera and propose an event fusion method (EFM) to enhance object detection in event-based vision systems. Each channel uses a different accumulation buffer to collect events from the event camera. We implement YOLOv7 for object detection, followed by a fusion algorithm. Our multichannel approach outperforms single-channel-based object detection by 0.7% in mean Average Precision (mAP) for detection overlapping ground truth with IOU = 0.5.
computervision, driven by artificial intelligence, has become pervasive in diverse applications such as self-driving cars and law enforcement. However, the susceptibility of these systems to attacks has raised signif...
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ISBN:
(数字)9798331506520
ISBN:
(纸本)9798331506537
computervision, driven by artificial intelligence, has become pervasive in diverse applications such as self-driving cars and law enforcement. However, the susceptibility of these systems to attacks has raised significant concerns among researchers. this paper addresses the vulnerability of image tagging algorithms, particularly focusing on misclassifications induced by autoencoders. We present experiments conducted on Amazon Rekognition, where we developed a specialized autoencoder to manipulate the latent space, forcing it to align with specific tags. By integrating this manipulated latent space with other images, we demonstrate the ability to increase the confidence of a specific tag on Amazon Rekognition, leading to more false positives of the chosen tag. Our study showcases a practical method to exploit Amazon’s Rekognition image tagging algorithm using a black box approach.
the proceedings contain 48 papers. the special focus in this conference is on computervision, Pattern Recognition, imageprocessing and graphics. the topics include: Parametric reshaping of humans in videos incorpora...
ISBN:
(纸本)9789811300196
the proceedings contain 48 papers. the special focus in this conference is on computervision, Pattern Recognition, imageprocessing and graphics. the topics include: Parametric reshaping of humans in videos incorporating motion retargeting;enhanced aggregated channel features detector for pedestrian detection using parameter optimisation and deep features;unsupervised segmentation of speech signals using Kernel-Gram matrices;Design of biorthogonal wavelet filters of DTCWT using factorization of halfband polynomials;single noisy image super resolution by minimizing nuclear norm in virtual sparse domain;near real-time correction of specular reflections in flash images using no-flash image prior;A method for detecting JPEG anti-forensics;an end-to-end deep learning framework for super-resolution based inpainting;saliency map improvement using edge-aware filtering;classification of human actions using 3-D convolutional neural networks: A hierarchical approach;A generative adversarial network for tone mapping HDR images;efficient clustering-based noise covariance estimation for maximum noise fraction;GMM based single depthimage super-resolution;patch similarity in transform domain for intensity/range image denoising with edge preservation;multi-modal image analysis for plant stress phenotyping;source classification using document images from smartphones and flatbed scanners;Homomorphic incremental directional averaging for noise suppression in SAR images;An EEG-based image annotation system;multimodal registration of retinal images;Dynamic class learning approach for smart CBIR;SmartTennisTV: Automatic indexing of tennis videos;exploring memory and time efficient neural networks for image captioning;dataset augmentation with synthetic images improves semantic segmentation;deep neural network for foreground object segmentation: An unsupervised approach;document image segmentation using deep features;flow-free video object segmentation.
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