This advertorial is sponsored by Intel®. "The long-term goal and true potential of AI is to replicate the complexity of human thinking at the macro level, and then surpass it to solve complex problems ”problems both well-documented and currently unimaginable in nature."1 Challenge Skin cancer has reached epidemic proportions in much of the world. A simple test is needed to … [Read more...] about Artificial Intelligence (AI) Helps with Skin Cancer Screening
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AI-Driven Test System Detects Bacteria In Water
This advertorial is sponsored by Intel®. Clean water and health care and school and food and tin roofs and cement floors, all of these things should constitute a set of basics that people must have as birthrights. 1 “ Paul Farmer, American Doctor, Anthropologist, Co-Founder,Partners In Health Challenge Obtaining clean water is a critical problem for much of the world's … [Read more...] about AI-Driven Test System Detects Bacteria In Water
Pedestrian Detection Using TensorFlow* on Intel’ Architecture
This advertorial is sponsored by Intel®. Abstract This paper explains the process to train and infer the pedestrian detection problem using the TensorFlow* deep learning framework on Intel® architecture. A transfer learning approach was used by taking the frozen weights from a Single Shot MultiBox Detector model with Inception* v2 topology trained on the Microsoft Common … [Read more...] about Pedestrian Detection Using TensorFlow* on Intel’ Architecture
Face Detection with Intel’ Distribution for Python*
This advertorial is sponsored by Intel®. Artificial Intelligence (AI) can be used to solve a wide range of problems, including those related to computer vision, such as image recognition, object detection, and medical imaging. In the present paper we show how to integrate OpenCV* (Open Source Computer Vision Library) with a neural network backend. In order to achieve this aim, … [Read more...] about Face Detection with Intel’ Distribution for Python*
Lower Numerical Precision Deep Learning Inference and Training
This advertorial is sponsored by Intel® Introduction Most commercial deep learning applications today use 32-bits of floating point precision (Æ’p32) for training and inference workloads. Various researchers have demonstrated that both deep learning training and inference can be performed with lower numerical precision, using 16-bit multipliers for training and 8-bit … [Read more...] about Lower Numerical Precision Deep Learning Inference and Training
