Archives for convolutional neural network - Page 2
We all have audienced the fantastic deep learning approaches that have regularly or empirically, demonstrated better than ever success each and every time in learning image representation tasks, such as image captioning, semantic segmentation, object detection, and so on. With a wide variety of convolutional neural networks on our hands, this has enabled us to…
The post Action Recognition Using Inflated 3D CNN appeared first on Analytics India Magazine.
EfficientNetV2 can train up to 11x faster than prior models, while being up to 6.8x smaller in parameter size.
The post Tech Behind Google’s New CNN, EfficientNetV2 appeared first on Analytics India Magazine.
Researchers at work find a way to enhance AI systems working through causal learning to overcome challenges.
The post Causal Representation Is Now Getting Its Due Importance In Machine Learning appeared first on Analytics India Magazine.
Researchers at work find a way to enhance AI systems working through causal learning to overcome challenges.
The post Causal Representation Is Now Getting Its Due Importance In Machine Learning appeared first on Analytics India Magazine.
RepVGG is a simple ConvNet architecture that combines multibranch topologies’ increased performance and the simplicity of VGG topology.
The post RepVGG: Can You Make Simple Architectures Great Again? appeared first on Analytics India Magazine.
Recently, Microsoft Research and the University of Montreal introduced a new mathematical framework that uses measure theory and integral operators to model attention architectures in neural networks. According to the researchers, the framework is proposed to quantify the regularity; in other words, the amount of smoothness of the attention operation. The attention mechanism is the…
The post Microsoft Introduces Mathematical Framework To Tune Up Attention Architectures appeared first on Analytics India Magazine.
Recently, Microsoft Research and the University of Montreal introduced a new mathematical framework that uses measure theory and integral operators to model attention architectures in neural networks. According to the researchers, the framework is proposed to quantify the regularity; in other words, the amount of smoothness of the attention operation. The attention mechanism is the…
The post Microsoft Introduces Mathematical Framework To Tune Up Attention Architectures appeared first on Analytics India Magazine.
India faces a drastic shortage of radiologists with just one radiologist available for 100,000 people living in the country. In comparison, this ratio is one to 10,000 in the US. With such a shortage of qualified professionals in the field, radiologists tend to see hundreds of X-rays in a day making the process error-prone. DeepTek,…
The post How This AI Firm Is Helping Radiologists Detect 20-different Pathologies With More Accuracy appeared first on Analytics India Magazine.
In computer vision applications, attention is either applied along with CNNs or used to replace certain components of these convolutional networks while keeping their overall structure in place. But convolutional architectures still remain dominant. Last week, a paper under double-blind review for ICLR 2021 enthused the ML community. The paper titled, ‘An image is worth…
The post Can Language Models Drive Computer Vision Models Out Of Business appeared first on Analytics India Magazine.
The conditional generative adversarial networks are an extension of DCGANs where the images are generated based on a certain condition. The generation of images can be conditional on a class which allows a particular type of images to be generated. Like a DCGAN architecture, cGAN also comprises a generator and a discriminator that is built…
The post How To Convert A Sketch Into Colored Image Using Conditional GAN appeared first on Analytics India Magazine.