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Found 12 papers, 1 papers with code
GeoFormer: A Vision and Sequence Transformer-based Approach for Greenhouse Gas Monitoring
Air pollution represents a pivotal environmental challenge globally, playing a major role in climate change via greenhouse gas emissions and negatively affecting the health of billions.
GeoViT: A Versatile Vision Transformer Architecture for Geospatial Image Analysis
Greenhouse gases are pivotal drivers of climate change, necessitating precise quantification and source identification to foster mitigation strategies.
Style Description based Text-to-Speech with Conditional Prosodic Layer Normalization based Diffusion GAN
In this paper, we present a Diffusion GAN based approach (Prosodic Diff-TTS) to generate the corresponding high-fidelity speech based on the style description and content text as an input to generate speech samples within only 4 denoising steps.
KL Regularized Normalization Framework for Low Resource Tasks
A lot of normalization techniques have been proposed but the success of normalization in low resource downstream NLP and speech tasks is limited.
One Shot Audio to Animated Video Generation
We propose a novel method OneShotAu2AV to generate an animated video of arbitrary length using an audio clip and a single unseen image of a person as an input.
Robust One Shot Audio to Video Generation
High-quality video generation with expressive facial movements is a challenging problem that involves complex learning steps for generative adversarial networks.
Multi Modal Adaptive Normalization for Audio to Video Generation
The multi-modal adaptive normalization uses the various features of audio and video such as Mel spectrogram, pitch, energy from audio signals and predicted keypoint heatmap/optical flow and a single image to learn the respective affine parameters to generate highly expressive video.
Few Shot Adaptive Normalization Driven Multi-Speaker Speech Synthesis
High quality multi-speaker speech synthesis while considering prosody and in a few shot manner is an area of active research with many real-world applications.
CatFedAvg: Optimising Communication-efficiency and Classification Accuracy in Federated Learning
Federated learning has allowed the training of statistical models over remote devices without the transfer of raw client data.
Fed-Focal Loss for imbalanced data classification in Federated Learning
The Federated Learning setting has a central server coordinating the training of a model on a network of devices.
Understanding Chat Messages for Sticker Recommendation in Messaging Apps
In the subsequent steps, we predict the message cluster instead of the message.
Advanced Bloom Filter Based Algorithms for Efficient Approximate Data De-Duplication in Streams
In this work, we present several novel algorithms for the problem of approximate detection of duplicates in data streams.
