Facial expressions are utilized often in the day to day communication and are considered significant as they can mirror the internal emotional states of a person. Automatic Facial Expression recognition (FER) systems ...
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ISBN:
(纸本)9783031126994;9783031127007
Facial expressions are utilized often in the day to day communication and are considered significant as they can mirror the internal emotional states of a person. Automatic Facial Expression recognition (FER) systems aim at classifying the facial images into various expressions. To do this task accurately, better feature descriptors are to be developed to effectively capture the facial information. In this regard, novel local texture based feature extraction technique, Petersen Graph based Binary pattern (PGBP), inspired by the Generalized Petersen Graph has been proposed. PGBP extracts three feature values in a 5x5 overlapping neighborhood. The experiments have been performed on MUG, TFEID and KDEF datasets with respect to six expressions in person independent setup. The experimental results demonstrated that the proposed method outperformed the existing methods in terms of recognition accuracy.
Cluster analysis is an unsupervised machine learning job of grouping objects based on some similarity measure. Among clustering algorithms, DBSCAN (Density Based Spatial Clustering of Application with Noise) contribut...
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The proceedings contain 242 papers. The topics discussed include: facial detection and recognition-based smart system on feature extraction using Raspberry Pi;a novel approach for text generation using RNN for languag...
ISBN:
(纸本)9798350343632
The proceedings contain 242 papers. The topics discussed include: facial detection and recognition-based smart system on feature extraction using Raspberry Pi;a novel approach for text generation using RNN for language modeling;analyzing resource allocation methods in fog computing for task scheduling: a study of heuristic and meta-heuristic approaches;IoT-enabled environmental intelligence: a smart monitoring system;sentiment analysis on restaurant review using machine learning algorithms;systematic review on various deep learning models for object detection in videos;analysis of a transmitter for IR-UWB standard;a comparative analysis of machine learning models for fake news detection;a DRA loaded quad band MIMO antenna with CSRR structure and metallic reflectors for mutual coupling reduction;and GCNN-based combined denoising and classification for improved MRI brain tumor identification.
The main job of auditing is to evaluate and review, and the huge and complex workload, as well as low tolerance for errors, are the characteristics of this work. However, with the development of technology and the exp...
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The method of Target recognition and location the key technology for team-accompanied robots to realize personnel-following navigation. In this paper, the target recognition algorithm based on YOLOv3 is combined with ...
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Early detection of crop diseases is an opportunity to optimize agricultural care and ultimately increase crop yields. Researchers studying machine learning are becoming increasingly interested in the automated detecti...
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With the rapid growth of technology, the era of network information has led to an increasing demand for communication among people, and the means of communication have also undergone earth shaking changes. To meet the...
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This article examines how the Internet of Things (IoT) is rapidly transforming the medical field. IoT technologies are revolutionizing patient care, increasing productivity, and boosting results in a variety of ways, ...
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The proceedings contain 328 papers. The topics discussed include: investigation and performance analysis of thermo electric cooling system for electric vehicle;design of neural network-based self-tuning control for hi...
ISBN:
(纸本)9798331509675
The proceedings contain 328 papers. The topics discussed include: investigation and performance analysis of thermo electric cooling system for electric vehicle;design of neural network-based self-tuning control for high step-forward converters in renewable energy-powered hybrid electric vehicles;applications of artificial intelligence and machine learning for accurate forecasting and optimization of renewable energy generation;enhanced thermo-physical properties of titanium dioxide nanofluids: applications in renewable energy systems and smart grid cooling technologies;viscosity behavior of multi-walled carbon nanotube nanofluids for advanced renewable energy cooling and storage systems;electric vehicle with enhanced power reliability and integrated charging technology;and adaptive rooftop solar system with optical wireless charging for electric vehicle batteries.
In machining process, 3D reverse engineering of mechanical system is an integral, highly important, and yet time consuming step to obtain parametric CAD models from 3D scans. Therefore, deep learning-based Scan-to-CAD...
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ISBN:
(纸本)9798350372977;9798350372984
In machining process, 3D reverse engineering of mechanical system is an integral, highly important, and yet time consuming step to obtain parametric CAD models from 3D scans. Therefore, deep learning-based Scan-to-CAD modeling can offer designers enormous editability to quickly modify CAD model, being able to parse all its structural compositions and design steps. In this paper, we propose a supervised boundary representation (BRep) detection network BRepDetNet from 3D scans of CC3D and ABC dataset. We have carefully annotated the similar to 50K and similar to 45K scans of both the datasets with appropriate topological relations (e.g., next, mate, previous) between the geometrical primitives (i.e., boundaries, junctions, loops, faces) of their BRep data structures. The proposed solution decomposes the Scan-to-CAD problem in Scan-to-BRep ensuring the right step towards feature-based modeling, and therefore, leveraging other existing BRep-to-CAD modeling methods. Our proposed Scan-to-BRep neural network learns to detect BRep boundaries and junctions by minimizing focal-loss and non-maximal suppression (NMS) during training time. Experimental results show that our BRepDetNet with NMS-Loss achieves impressive results.
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