Accurate class and early detection of mind tumour is of maximum significance to facilitate powerful treatment planning to improve affected person consequences. This work offers a novel technique makes use of convoluti...
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Neural networks are now the standard solution to many computer vision problems. Their generalization ability enables them to successfully address various tasks in computational photography, such as enhancement, restor...
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ISBN:
(纸本)9783031728440;9783031728457
Neural networks are now the standard solution to many computer vision problems. Their generalization ability enables them to successfully address various tasks in computational photography, such as enhancement, restoration, and color constancy. However, their performance is highly dependent on the illumination conditions of the training images. When faced with test images under different illuminant conditions, these networks often struggle to perform their tasks correctly. In this paper, we investigate the efficacy of illuminant equivariant neural networks for the illuminant estimation task, which is crucial for computational color constancy. These networks are equivariant to the photometric transformations that characterize changes in lighting conditions. They achieve this capability through mathematical derivation rather than specific augmentation during training. We implemented the equivariant versions of state-of-the-art neural networks for illuminant estimation and tested them on the NUS dataset. The results demonstrate that the equivariant networks maintain stable performance even with significant changes in illumination, whereas the original standard networks exhibit a serious degradation in their accuracy.
From September 16 to 19, 2024, an internationalsymposium to celebrate the centennial of the discovery of the gastrula organizer by Hans Spemann and Hilde Mangold, was held at the University of Freiburg, Germany, wher...
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From September 16 to 19, 2024, an internationalsymposium to celebrate the centennial of the discovery of the gastrula organizer by Hans Spemann and Hilde Mangold, was held at the University of Freiburg, Germany, where they studied embryology. There were 41 plenary lectures, 11 short talks, and 182 poster presentations, with more than 300 participants from 23 countries. The symposium covered research topics broadly related to developmental, cell, genome, and evolutionary biology, mainly focused on early animal development. In addition to in vivo studies on topics such as gastrulation, embryonic patterning, cell polarity, and morphogenesis, recent studies using gastruloids and organoids, which recapitulate embryogenesis and organogenesis in in vitro cell culture, were also presented at this symposium, entitled Self-Organization in Biology. Most of the reported studies used vertebrate models such as mice, frogs, and zebrafish;however, evolutionary studies involving invertebrate and plant models were also presented. Presentations employing traditional methods such as cell transplantation and phenotype screening, and state-of-the-art technologies such as single-cell omics, high-resolution imaging, and computational analysis showed that experimental embryology has a long history, to which studies of the organizer have contributed significantly. Here we discuss memorable aspects of the symposium in the hope that this report will encourage young scientists to actively participate in face-to-face international conferences.
Creating natural language descriptions or captions for images is a formidable task that requires a combination of computer vision techniques to understand image content and natural language processing models to expres...
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In recent years, Given the speed at which bioinformatics and computer technologies are developing, computer-Aided Drug Design (CADD) has made tremendous progress. CADD involves the rational design of drugs by calculat...
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Recently, with increased use of mobile phones, it has transformed into a multibillion-dollar Short Message Service or SMS. However, the drop in the cost of messaging services has led to an increased number of unsolici...
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In the realm of recommendation systems, achieving real-time performance in embedding similarity tasks is often hindered by the limitations of traditional Top-K sparse matrix-vector multiplication (SpMV) methods, which...
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ASR is an effectual approach, which converts human speech into computer actions or text format. It involves extracting and determining the noise feature, the audio model, and the language model. The extraction and det...
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Social media platforms like Instagram, Twitter, and Facebook have completely changed our world. People today exhibit a kind of digital character and are more linked than ever. While social media undoubtedly offers man...
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With the advancement of technologies, different methods are currently being used for converting spoken language into text. These systems offer a hands-free alternative to traditional input methods, especially for indi...
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