By Atharva Agrawal Growing up in the Tiger Capital of India, Nagpur, a city surrounded by some of the country’s most eminent wildlife sanctuaries, including Pen ...

As sensor data overwhelms the cloud, Innatera’s neuromorphic chips bring always-on, ultra-low-power AI directly to the edge. But how?

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...

Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural ...

1 Guangzhou Railway Polytechnic, Guangzhou, China. 2 School of Intelligent Construction and Civil Engineering, Zhongyuan University of Technology, Zhengzhou, China. 3 Research Center for Wind ...

🎮 Train a Deep Q-Learning agent using TensorFlow to master Atari Breakout with efficient experience replay and modular architecture for easy customization.

1 College of Electronic Science and Technology, National University of Defense Technology, Changsha, China 2 College of Electronics and Internet of Things, Chongqing Polytechnic University of ...

Abstract: Convolutional Neural Networks or CNNs are one of the newest powerful tools in various tasks of computer vision such as image classification or object detection providing the highest accuracy ...

Deep learning-based image steganalysis has progressed in recent times, with efforts more concerted toward prioritizing detection accuracy over lightweight frameworks. In the context of AI-driven ...

ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...