the proceedings contain 32 papers. the topics discussed include: facial expression recognition using multi-feature concatenation of local face components and hierarchical SVM;performance evaluation of temporal and spa...
ISBN:
(纸本)9781665426596
the proceedings contain 32 papers. the topics discussed include: facial expression recognition using multi-feature concatenation of local face components and hierarchical SVM;performance evaluation of temporal and spatial-temporal convolutional neural networks for land-cover classification (a case study in Shahrekord, Iran);a graph-based density peaks method by employing shortest path for data clustering;ACO-based intrusion detection method in computer networks using fuzzy association rules;discriminating the original region from the duplicated in copy-move forgery;efficient scramble for quasi-random numbers in Monte Carlo computations;pyramidal connected component labeling by irregular graph pyramid;optimum HEVC quantization parameter for cloud gaming;and person re-identification using ensemble of networks on pose transferred images.
the proceedings contain 111 papers. the topics discussed include: a fast scheme for multiscale signal denoising;color scratches removal using human perception;self-similarity of images in the Fourier domain, with appl...
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ISBN:
(纸本)3540698116
the proceedings contain 111 papers. the topics discussed include: a fast scheme for multiscale signal denoising;color scratches removal using human perception;self-similarity of images in the Fourier domain, with applications to MRI;a simple scaling algorithm based on areas pixels;a new method for sharpening color images using fuzzy approach;wavelet noise reduction based on energy features;fast exact area image upsampling with natural biquadratic histosplines;evolving fuzzy modeling of an uncalibrated visual servoing system;alternative methods for counting overlapping grains in digital images;image affine inpainting;segmentation of hyperspectral images for the detection of rotten mandarins;FPGA implementation of parallel alpha-beta associative memories;from narrow to broad band design and selection in hyperspectral images;and improving the border detection and image enhancement algorithms in tableau.
Focusing on a field of intelligent computer imagerecognition, a BP neural network model which is rooted in genetic algorithm (GA) fine-tuning is presented in my study. Aiming at the limitations faced by traditional i...
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this paper provides a concise exploration of speaker recognition using DL, focusing on the analysis of speech signals and their transformation through Fourier analysis. the study employs Fast Fourier Transform to quan...
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this paper provides a concise exploration of speaker recognition using DL, focusing on the analysis of speech signals and their transformation through Fourier analysis. the study employs Fast Fourier Transform to quantify dissimilarities between speakers and validates its efficacy in speaker recognition. As human voices possess distinct characteristics, voice-based recognition emerges as a valuable biometric technique. this research delves into the realm of Speaker recognition technology. Spectrum analysis involves converting time-domain signals into frequency-domain representations using Fourier Transform and Convolutional neural network (CNN). Fast Fourier Transform (FFT) is harnessed to extract frequency content from analogue signals. DNN algorithms play a pivotal role in speaker classification. through these approaches, the paper advances our understanding of speaker recognition within the domain of DL.
A GAN-based imagerecognition algorithm is presented to solve these problems. Firstly, the GAN frame is composed of a generator and a discriminator. the generator can produce real images or remove noise by learning th...
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Even withthe rapid advancement of technology, using a television still requires a physical remote control. Apart from occasionally losing sight of the television remote control, we also sometimes run out of batteries...
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Even withthe rapid advancement of technology, using a television still requires a physical remote control. Apart from occasionally losing sight of the television remote control, we also sometimes run out of batteries. the goal is to discover an effective way of controlling television and develop 3D hand gesture-based smart television control using Gated Recurrent Unit (GRU). the results of the research show that hand gesture recognition-based interface technology is capable of performing the majority of smart TV operations. It is a comfortable and delightful experience for consumers. the existing research features static image gesture recognition with predefined models for training in addition to the existing research the proposed model features sample video dataset, Custom design with Gated Recurrent Unit. the suggested model is trained using five hand gestures. the camera positioned on the TV continually records the motions. Each gesture is associated with a certain command. the proposed model has achieved an accuracy of about 94% in recognizing the gestures.
this paper proposes a pig image classification model based on convolutional neural network (CNN), named Pig imagerecognition Model (PIRM). the model uses regional suggestion network (RPN) to generate candidate region...
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Chat Analyzer is an intelligent system that employs natural language processing (NLP) techniques to analyze and extract insights from conversational texts. By utilizing sentiment analysis, topic modeling, intent recog...
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Chat Analyzer is an intelligent system that employs natural language processing (NLP) techniques to analyze and extract insights from conversational texts. By utilizing sentiment analysis, topic modeling, intent recognition, and entity extraction, it enables businesses and researchers to gain valuable information from chat conversations. the system finds applications in customer support analysis, social media monitoring, market research, and conversational AI development, facilitating improved decision-making and customer satisfaction. the Chat Analyzer system leverages state-of-the-art NLP techniques and machine learning algorithms to provide an intelligent and comprehensive analysis of chat data. It incorporates various components such as text preprocessing, sentiment analysis, topic modeling, intent recognition, and entity extraction to facilitate a thorough examination of the conversational content. the text preprocessing module performs essential tasks such as tokenization, stemming, and stop-word removal to enhance the quality of subsequent analyses. the sentiment analysis component employs machine learning models to detect and classify the underlying sentiment expressed in the chat conversations, providing insights into the emotional tone of the dialogue.
Withthe explosive growth of multimedia data, how to effectively extract information from images and texts and realize the integration of the two has become a research hotspot. this paper discusses the application of ...
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