Facial Expression recognition (FER) in the wild has become an increasingly significant and focused area within computervision, with many studies tackling different aspects to improve its recognition accuracy. This pa...
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ISBN:
(数字)9781665495486
ISBN:
(纸本)9781665495486
Facial Expression recognition (FER) in the wild has become an increasingly significant and focused area within computervision, with many studies tackling different aspects to improve its recognition accuracy. This paper utilizes RAF-DB and AffectNet as the two leading datasets in the scene and compares the different experimental dataset configurations to state-of-the-art techniques referred to as Amend Representation Module (ARM) and Self-Cure Network (SCN). The paper demonstrates how different dataset configurations should be the main focal point of improving the FER task and how there cannot be significant improvements in the FER task with a lack of a favorable dataset.
An essential feature of the intelligent transportation system is the automatic detection and recognition of license plate information. The e-payment systems for parking and toll collection in traffic control security ...
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Proximal Object detection using computervision is one of the important domains that comprehends the users or objects in front of them through vision Glasses to recognise objects and inform the Visually Impaired (VI)....
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The surface integrity, rot degree, mechanical damage, rupture, scar and other states of sand sugar orange fruit can be reflected from the surface defects of sand sugar orange. The surface defects of sand sugar orange ...
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This paper uses the Theory of Characteristic Modes (TCM) to study the radiation pattern stability and reduce the size of a circular planar antenna. A comparative study of different shapes is conducted to carry out hig...
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Aerospace engineering design and manufacturing greatly rely on accurate and efficient plane wing diagram data extraction. This paper introduces an innovative technique for automating the process using state-of-the-art...
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With the continuous progress of society, the problem of traffic congestion is becoming increasingly serious. However, when an unmanned vehicle is driving on the highway, it is unavoidable to encounter situations such ...
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We study the problem of quantizing N sorted, scalar datapoints with a fixed codebook containing K entries that are allowed to be rescaled. The problem is defined as finding the optimal scaling factor a and the datapoi...
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ISBN:
(纸本)9781665445092
We study the problem of quantizing N sorted, scalar datapoints with a fixed codebook containing K entries that are allowed to be rescaled. The problem is defined as finding the optimal scaling factor a and the datapoint assignments into the a-scaled codebook to minimize the squared error between original and quantized points. Previously, the globally optimal algorithms for this problem were derived only for certain codebooks (binary and ternary) or under the assumption of certain distributions (Gaussian, Laplacian). By studying the properties of the optimal quantizer, we derive an O(NK logK) algorithm that is guaranteed to find the optimal quantization parameters for any fixed codebook regardless of data distribution. We apply our algorithm to synthetic and real-world neural network quantization problems and demonstrate the effectiveness of our approach.
Human Activity recognition(HAR) is an essential field of research with numerous applications in human-computer interaction, security, surveillance, and healthcare. Even with significant improvements, recognizing activ...
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The innovative generation of vector graphics with fine-grained images using Artificial Intelligence has become an important task in edge extraction. In this paper, we take Qiang embroidery image as an example due to i...
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