Emotion recognition is challenging due to the emotional gap between emotions and audio-visual features. Motivated by the powerful feature learning ability of deep neural networks, this paper proposes ...

A cutting-edge system for real-time audio-visual speech synthesis using deep learning. This project takes text, a voice sample, and an image or video to generate synchronized speech with lifelike lip ...

•Built a real-time driver drowsiness detection system using Flask, TensorFlow, and OpenCV for live video monitoring, incorporating Haar cascades for face and eye detection. •Implemented an alert ...

The new ImageBind model combines text, audio, visual, movement, thermal, and depth data. It’s only a research project but shows how future AI models could be able to generate multisensory content.

Using telemetry garnered from the custom personal/team model training scheme explained above, Microsoft shut down that capability after noticing how much better the deep learning approach is. "All ...

Microsoft announced on-device training of machine language models with the open source ONNX Runtime (ORT). The ORT is a cross-platform machine-learning model accelerator, providing an interface to ...

Deep Learning A-Z 2025: Neural Networks, AI, and ChatGPT Prize. Offered by Udemy, this course is taught by Kirill Eremenko and Hadelin de Ponteves and focuses on practical deep learning ...

Abstract: Emotion recognition is challenging due to the emotional gap between emotions and audio-visual features. Motivated by the powerful feature learning ability of deep neural networks, this paper ...