Multilingual Automatic Speech Recognition with word-level timestamps and confidence
-
Updated
Nov 4, 2024 - Python
Multilingual Automatic Speech Recognition with word-level timestamps and confidence
TF2 Deep FloorPlan Recognition using a Multi-task Network with Room-boundary-Guided Attention. Enable tensorboard, quantization, flask, tflite, docker, github actions and google colab.
This repository contain various types of attention mechanism like Bahdanau , Soft attention , Additive Attention , Hierarchical Attention etc in Pytorch, Tensorflow, Keras
Pytorch Implementation of "Adaptive Co-attention Network for Named Entity Recognition in Tweets" (AAAI 2018)
[TMI 2019] Attention to Lesion: Lesion-Aware Convolutional Neural Network for Retinal Optical Coherence Tomography Image Classification
Image captioning using beam search heuristic on top of the encoder-decoder based architecture
RSANet: Recurrent Slice-wise Attention Network for Multiple Sclerosis Lesion Segmentation (MICCAI 2019)
[CoRL 2023] Context-Aware Deep Reinforcement Learning for Autonomous Robotic Navigation in Unknown Area - - Public code and model
Speech recognition model for recognising Macedonian spoken language.
Google Research 3rd YouTube-8M Video Understanding Challenge 2019. Temporal localization of topics within video. International Conference on Computer Vision (ICCV) 2019.
Using attention network to extend image quality assessment algorithms for video quality assessment
Gated-ViGAT. Code and data for our paper: N. Gkalelis, D. Daskalakis, V. Mezaris, "Gated-ViGAT: Efficient bottom-up event recognition and explanation using a new frame selection policy and gating mechanism", IEEE International Symposium on Multimedia (ISM), Naples, Italy, Dec. 2022.
Sequence 2 Sequence with Attention Mechanisms in Tensorflow v2
An attention network for predicting peptide lengths (and other features) from mass spectrometry data.
A TensorFlow 2.0 Implementation of the Transformer: Attention Is All You Need
[IEEE Access 2024] DA-Net: Dual Attention Network for Haze Removal in Remote Sensing Image
This work proposes a feature refined end-to-end tracking framework with a balanced performance using a high-level feature refine tracking framework. The feature refine module enhances the target feature representation power that allows the network to capture salient information to locate the target. The attention module is employed inside the fe…
High Dynamic Range Image Synthesis via Attention Non-Local Network
Python 3 supported version for DySAT
Graphs are a general language for describing and analyzing entities with relations/interactions.
Add a description, image, and links to the attention-network topic page so that developers can more easily learn about it.
To associate your repository with the attention-network topic, visit your repo's landing page and select "manage topics."