Make Your Enterprise AI-Ready technologies which together empower rapid end to end business process accelerate digital era. 90% of companies we surveyed are using AI to elevate performance, many in business functions beyond IT.
A cancer that develops in the breast cells and progresses in stages. Few early symptoms may include new lump in the underarm or in breast, itching or discharge from the nipples, and skin texture change of the nipple or breast.
Try MeObject detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. Well-researched domains of object detection include face detection and pedestrian detection.
Try MeWe use transfer learning for a new and important type of unstructured audio data to build a sound classifier by using deep Learning. The model takes a waveform represented as 16 kHz samples in the range [-1.0, 1.0], frames it in windows of 0.96 seconds and hop of 0.48 seconds, and then runs the core of the model to extract the embeddings on a batch of these frames.
Try MeThis is what puts the "deep" in deep learning. Each layer categorizes some kind of information, refines it, and passes it along to the next. The parallel computing nature of GPUs accelerates this process to enable breakthroughs like facial recognition, real-time voice translation, and self-driving cars.
Large-scale automatic speech recognition is the first and most convincing successful case of deep learning.
Deep learning-based image recognition has become "superhuman", producing more accurate results than human contestants.
Neural networks have been used for implementing language models. we improve machine translation and language modeling
We Build Data Driven with our Intellectual things is a key aspect for economic development in AI. negative sampling and word embedding
A large percentage of candidate drugs fail to win regulatory approval. These failures are caused by insufficient efficacy (on-target effect).
Deep RL has been used to approximate the value of possible direct marketing actions, defined in terms of RFM variables
Recommendation systems have used deep learning to extract meaningful features for a latent factor model for content-based music and journal recommendations
Finding the appropriate mobile audience for mobile advertising is always challenging, since many data points must be considered and analyzed before a target.
An autoencoder ANN was used in bioinformatics, to predict gene ontology annotations and gene-function relationships with electronic health record data.
Deep learning has been successfully applied to inverse problems such as denoising, super-resolution, inpainting, and film colorization, Effective Image Restoration
Financial fraud detection by using Deep learning is being successfully applied to financial fraud detection, tax evasion detection,and anti-money laundering.
Defense applied deep learning to train robots in new tasks through observation the enivorement realistic simulators contributes to the acceleration of research
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