Tumors are aberrant tissue growths that can develop in any body organ. Numerous varieties of human tumors have been discovered in recent years, including brain, bone, and lung. imageprocessing is essential in tumor a...
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image segmentation is a prime domain of computer vision backed by a huge amount of research involving both imageprocessing-based algorithm and learning-based techniques. Due to this there is an upsurge in different s...
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This survey paper examines the transformative role of medical imaging in healthcare and the integration of AI systems for diagnosis and treatment. The emergence of HealthTech startups and AI algorithms highlights the ...
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To balance the accuracy and speed of image fusion, a lightweight infrared and visible image fusion algorithm is proposed in this paper. Firstly, to improve the feature extraction capability, ECA attention is introduce...
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Through the in-depth analysis of artificial neural network algorithm technology, particle swarm algorithm technology, and image matching algorithm, the article briefly analyzes the theoretical principle of the algorit...
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In recent years, there has been a growing interest in the development of in vitro models to predict cellular behavior within living organisms. Mathematical models, based on differential equations and associated numeri...
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The proceedings contain 396 papers. The topics discussed include: development of an IoT enabled smart children tracking and monitoring system using map location services;HMLM: an intelligent artificial intelligence as...
ISBN:
(纸本)9798331543617
The proceedings contain 396 papers. The topics discussed include: development of an IoT enabled smart children tracking and monitoring system using map location services;HMLM: an intelligent artificial intelligence assisted strategy to identify UPI frauds based on hybrid Markov learning methodology;data-driven insights into automotive customer complaints: a machine learning approach to predictive analytics;integrating predictive analytics and deep learning for vehicle safety incident forecasting;analyzing the health status of people in rural areas using machine learning algorithms;machine learning based approach using hand gestures for mouse and video control;experimental analysis of artificial intelligence powered adaptive learning methodology using enhanced deep learning principle;a comprehensive analysis of imageprocessing methods for agricultural product quality control;and convolutional neural network-based multi-fruit classification and quality grading with a Gradio interface.
Skin cancer is a severe health issue. Thus, the major concern of physicians is to investigate a precise clinical diagnosis. At present, some mechanisms are developed in the area of imageprocessing with the help of al...
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Efficient transfer learning algorithms are key to the success of foundation models on diverse downstream tasks even with limited data. Recent works of Basu et al. (2023) and Kaba et al. (2022) propose group averaging ...
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ISBN:
(纸本)9781713899921
Efficient transfer learning algorithms are key to the success of foundation models on diverse downstream tasks even with limited data. Recent works of Basu et al. (2023) and Kaba et al. (2022) propose group averaging (equitune) and optimization-based methods, respectively, over features from group-transformed inputs to obtain equivariant outputs from non-equivariant neural networks. While Kaba et al. (2022) are only concerned with training from scratch, we find that equitune performs poorly on equivariant zero-shot tasks despite good finetuning results. We hypothesize that this is because pretrained models provide better quality features for certain transformations than others and simply averaging them is deleterious. Hence, we propose lambda-equitune that averages the features using importance weights, lambda s. These weights are learned directly from the data using a small neural network, leading to excellent zero-shot and finetuned results that outperform equitune. Further, we prove that lambda-equitune is equivariant and a universal approximator of equivariant functions. Additionally, we show that the method of Kaba et al. (2022) used with appropriate loss functions, which we call equizero, also gives excellent zero-shot and finetuned performance. Both equitune and equizero are special cases of lambda-equitune. To show the simplicity and generality of our method, we validate on a wide range of diverse applications and models such as 1) image classification using CLIP, 2) deep Q-learning, 3) fairness in natural language generation (NLG), 4) compositional generalization in languages, and 5) image classification using pretrained CNNs such as Resnet and Alexnet.
image deraining typically involves synthesizing low-quality degraded data for training using a predefined degraded model of a single weather condition. While in real world scenarios, varying rain intensities result in...
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