Multilingual Automatic Speech Recognition with word-level timestamps and confidence
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Updated
Nov 25, 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
[CoRL 2023] Context-Aware Deep Reinforcement Learning for Autonomous Robotic Navigation in Unknown Area - - Public code and model
RSANet: Recurrent Slice-wise Attention Network for Multiple Sclerosis Lesion Segmentation (MICCAI 2019)
Google Research 3rd YouTube-8M Video Understanding Challenge 2019. Temporal localization of topics within video. International Conference on Computer Vision (ICCV) 2019.
Image captioning using beam search heuristic on top of the encoder-decoder based architecture
Python 3 supported version for DySAT
High Dynamic Range Image Synthesis via Attention Non-Local Network
This is the official source code of our IEA/AIE 2021 paper
locality-aware invariant Point Attention-based RNA ScorEr
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…
Speech recognition model for recognising Macedonian spoken language.
Efficient Visual Tracking with Stacked Channel-Spatial Attention Learning
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.
Using attention network to extend image quality assessment algorithms for video quality assessment
A TensorFlow 2.0 Implementation of the Transformer: Attention Is All You Need
Sequence 2 Sequence with Attention Mechanisms in Tensorflow v2
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